tag:blogger.com,1999:blog-90938899122153502292024-03-27T12:56:45.284+05:30Learning Algorithms with Rachit Jain<code> This is my blog dedicated to competitive programming. I write about interesting data structures, algorithms and beautiful problems that have awesome analysis and thus offer great learning. </code>Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.comBlogger25125tag:blogger.com,1999:blog-9093889912215350229.post-40673236815780742042019-02-17T12:09:00.003+05:302019-12-27T17:36:16.682+05:30Art of Time Management | Achieving Multiple Things in Life<div dir="ltr" style="text-align: left;" trbidi="on">
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rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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Tags:</b> time management, success, health, money, education</span><br />
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<span style="font-family: Trebuchet MS, sans-serif;">Hey Guys!</span><br />
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<span style="font-family: Trebuchet MS, sans-serif;">Its me Rachit after a long time! </span><br />
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<span style="font-family: Trebuchet MS, sans-serif;">After 1700+ upvotes on Quora, I finally created a video on Time Management and Achieving Multiple Things in Life. </span><br />
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<img alt="Pinned Answer
How did you manage competitive programming with
development and projects in your undergrad?
Rachit Jain, Software Engineer at Microsoft (2017-present)
Answered Dec 12, 2017 • Upvoted by Bhavik Dhandhalya, Hacker, Problem Setter on
SPOJ & HackerEarth, ACM ICPC 2016 Participant
I am rachitjain on Codeforces, rachitiitr on Codechef. With all due respect to
Satyaki, I found his answer did not include the multiple aspects of a practical life.
Eg: "8 hours of lecture", we all ... (more)
Pulkit Goel and Shaumik Daityari upvoted this
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" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: white; border: 1px dashed rgb(191, 191, 191); font-family: "Segoe UI", "Segoe UI Web", Arial, Verdana, sans-serif; font-size: 12px; height: 233px; margin: 0px; padding: 0px; user-select: text; width: 480px;" /><br />
<span style="font-family: Trebuchet MS, sans-serif;">Quora Profile: <a href="https://www.quora.com/profile/Rachit-Jain-19">here</a></span><br />
<span style="font-family: Trebuchet MS, sans-serif;"><br /></span>
<span style="font-family: Trebuchet MS, sans-serif;">YouTube Video is out, so head on to YouTube to watch it.</span><br />
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<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfs373_mXAXk4GtvErjWSyuJfK5pXorrw6ZJ-DZOH1wzL25JRbeBzFxHNpsElOox3gpNGaM4eCcH2zJJ-Uqqpe4O719eo0XuFvSbs25dBRqqevAq12hWXgbo4CM_0i0aYQwXs_S1wTZvla/s1600/banner8.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="711" data-original-width="1275" height="178" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfs373_mXAXk4GtvErjWSyuJfK5pXorrw6ZJ-DZOH1wzL25JRbeBzFxHNpsElOox3gpNGaM4eCcH2zJJ-Uqqpe4O719eo0XuFvSbs25dBRqqevAq12hWXgbo4CM_0i0aYQwXs_S1wTZvla/s320/banner8.png" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<span style="text-align: left;">YouTube Video: </span><a href="https://www.youtube.com/watch?v=Sio32La-aaE" style="text-align: left;">here</a></div>
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<span style="font-family: Trebuchet MS, sans-serif;"><br /></span>
<span style="font-family: Trebuchet MS, sans-serif;">You can watch the video, and here are few important points worth mentioning:</span><br />
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: white; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<ul class="BulletListStyle1 BCX0 SCXO47171047" role="list" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; cursor: text; margin: 6px 0px 0px; overflow: visible; padding: 0px; text-align: left; user-select: text;">
<li><span style="font-family: Trebuchet MS, sans-serif;"><u><b><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US">When to study for your branch</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></b></u></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">10-14 days before </span><span class="ContextualSpellingAndGrammarError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">mid terms</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">, end terms</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">If not doing CP in class, I would actually try to understand what's going on<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">Upsolving</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> helps pick up new things faster</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Connecting dots<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">Whats</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> the syllabus</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Build a story<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Ok three types of motors, for every motor the principle behind its function<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">Their </span><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">characterstic</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> curves, different use scenarios</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">Intuition about what's more important<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">Study in priority<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">Talking to profs about some </span><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">xyz</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> topic</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Ask friends who regularly go to class<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">See tutorial/assignment solutions – solve by <span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">tihnking</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> and seeing</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">Art of writing answers – keep in mind that even a </span><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">comman</span><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;"> man should be able to understand this</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
</ul>
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<div class="Paragraph BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; overflow-wrap: break-word; padding: 0px; user-select: text; vertical-align: baseline;" xml:lang="EN-US">
<br /></div>
</div>
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<div class="Paragraph BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; overflow-wrap: break-word; padding: 0px; user-select: text; vertical-align: baseline;" xml:lang="EN-US">
<br /></div>
</div>
</div>
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: white; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<ul class="BulletListStyle1 BCX0 SCXO47171047" role="list" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; cursor: text; margin: 6px 0px 0px; overflow: visible; padding: 0px; text-align: left; user-select: text;">
<li><span style="font-family: Trebuchet MS, sans-serif;"><b><u><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US">How to time-manage Competitive Programming</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></u></b></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">Utilizing the gaps<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">Eating alone in mess/canteen<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Walking / Riding bicycle to the Lecture hall<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">During the lecture itself<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">While taking showers – works like a charm<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Retrospection <span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Fitness – two different personalities<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
</ul>
<li class="OutlineElement Ltr BCX0 SCXO47171047" data-aria-level="2" data-aria-posinset="1" role="listitem" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; display: block; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text; vertical-align: baseline;"><div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<div class="Paragraph BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; overflow-wrap: break-word; padding: 0px; user-select: text; vertical-align: baseline;" xml:lang="EN-US">
<br /></div>
</div>
</li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><b><u><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US">When to do Development</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></u></b></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">In span of months <span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">HTML, CSS, JavaScript – w3schools [2 weeks]<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Django REST APIs [3 weeks] <span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Database [1 week]<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;">Project like timetable app<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">API to login, load timetable, edit timetable, save timetable<span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
</ul>
</ul>
</div>
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: white; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<ul class="BulletListStyle1 BCX0 SCXO47171047" role="list" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; cursor: text; margin: 6px 0px 0px; overflow: visible; padding: 0px; text-align: left; user-select: text;">
<li class="OutlineElement Ltr BCX0 SCXO47171047" data-aria-level="2" data-aria-posinset="5" role="listitem" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; display: block; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text; vertical-align: baseline;"><div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<div class="Paragraph BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; overflow-wrap: break-word; padding: 0px; user-select: text; vertical-align: baseline;" xml:lang="EN-US">
<br /></div>
</div>
<div class="OutlineElement Ltr BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; margin: 0px 0px 0px 24px; overflow: visible; padding: 0px; position: relative; user-select: text;">
<div class="Paragraph BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; overflow-wrap: break-word; padding: 0px; user-select: text; vertical-align: baseline;" xml:lang="EN-US">
<br /></div>
</div>
</li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><b><u><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US">When to do Machine Learning</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></u></b></span></li>
<ul>
<li><span style="font-family: Trebuchet MS, sans-serif;">Preferred in 3<span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US"><span class="NormalTextRun BCX0 SCXO47171047" data-fontsize="11" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text; vertical-align: super;">rd</span></span><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US"> year, 4</span><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US"><span class="NormalTextRun BCX0 SCXO47171047" data-fontsize="11" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text; vertical-align: super;">th</span></span><span class="TextRun BCX0 SCXO47171047" lang="EN-US" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-variant-ligatures: none !important; line-height: 18px; margin: 0px; padding: 0px; user-select: text;" xml:lang="EN-US"> year</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
<li><span style="font-family: Trebuchet MS, sans-serif;"><span class="NormalTextRun BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; margin: 0px; padding: 0px; user-select: text;">BTech project, </span><span class="SpellingError BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: inherit; background-image: url("data:image/gif; background-position: left bottom; background-repeat: repeat-x; border-bottom: 1px solid transparent; margin: 0px; padding: 0px; user-select: text;">etc</span><span class="EOP BCX0 SCXO47171047" style="-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; line-height: 18px; margin: 0px; padding: 0px; user-select: text;"> </span></span></li>
</ul>
</ul>
</div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com3tag:blogger.com,1999:blog-9093889912215350229.post-90572169072574726422018-11-24T12:27:00.001+05:302019-12-27T17:36:19.708+05:30Cracking the Google Interview | Software Engineer reveals tips & secrets<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: google, google job,placement, interviews, data-structures, algorithms<br />
<br />
Hi! Today I will write about some tips, tricks and hacks I have found from my experience in attempting recruitment tests, interviews. <br />
<br />
I will begin by giving a brief introduction about myself.<br />
I have done B. Tech. in <b>Electrical Engineering </b>from <b>IIT Roorkee.</b> I have graduated in 2017, and now working in <b>Microsoft </b>for over 18+ months<b>.</b><br />
<br />
I started off competitive programming in <b>2-2</b>(2nd Year 2nd Semester)<b>. </b>So I had around 1.5 years of experience in competitive programming while I was sitting for placement tests. Having a strong background in competitive programming really saves your ass while others keep reading geeksforgeeks to prepare themselves.<br />
<br />
You can subscribe to my programming YouTube channel, <a href="https://www.youtube.com/c/RachitJain">"Algorithms with Rachit" here</a>.<br />
<br />
"New Video Every Week" - Subscribe to my <a href="https://www.youtube.com/c/RachitJain">YouTube channel for free</a>.<br />
<br />
<br />
<b><span style="font-size: large;">How to crack the Google interviews and get a decent job?</span></b><br />
<b><span style="font-size: large;"><br /></span></b>
Here is the YouTube video of 12 mins where I share the complete journey of what exactly happens in a Google Interview, what kind of questions they ask, from where to prepare, and possible mistakes you might be making despite having good skills and getting rejected.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen="" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/H9PVV-hMKzs/0.jpg" frameborder="0" height="266" src="https://www.youtube.com/embed/H9PVV-hMKzs?feature=player_embedded" width="320"></iframe></div>
<div class="separator" style="clear: both; text-align: center;">
<b><u>Video: Software Engineer talks about cracking Google | Tips & Story of cracking Google</u></b></div>
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<br /></div>
<br />
After watching this, you already can see the links in video description. Anyway, if you are lazy, here is what you have to do next.<br />
See <b><u>the mistakes you will be making </u></b>despite being good at tech skills and hence getting rejected.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<b><u><iframe allowfullscreen="" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/aqjy-XYmNi8/0.jpg" frameborder="0" height="266" src="https://www.youtube.com/embed/aqjy-XYmNi8?feature=player_embedded" width="320"></iframe></u></b></div>
<div class="separator" style="clear: both; text-align: center;">
<b><u>Video: Why Google rejects great coders in Software Interviews?</u></b></div>
<div class="separator" style="clear: both; text-align: center;">
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<div class="separator" style="clear: both; text-align: center;">
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Now, comes the part about <b><u>what you have to study</u></b>. For that have a look at -<br />
<br />
<iframe allowfullscreen="" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/LK02ZPv9vdk/0.jpg" frameborder="0" height="266" src="https://www.youtube.com/embed/LK02ZPv9vdk?feature=player_embedded" width="320"></iframe><br />
<div style="text-align: justify;">
<b style="text-align: center;"> <u>Video: Why Google rejects great coders in Software Interviews?</u></b></div>
<div style="text-align: justify;">
<b style="text-align: center;"><u><br /></u></b></div>
<div style="text-align: justify;">
<b style="text-align: center;"><span style="color: red;">To learn more on how to solve Coding Interview Problems, I launched a playlist where I pickup famous and interesting Interview questions and explain the approach and then the code in C++ to solve them. </span></b></div>
<div style="text-align: justify;">
<b style="text-align: center;"><br /></b></div>
<div style="text-align: justify;">
<b style="text-align: center;">"Famous Coding Interview Problems and their Solutions" - </b><span style="text-align: center;">click <a href="https://www.blogger.com/%22https://www.youtube.com/playlist?list=PLfBJlB6T2eOshO8-LYaMt-Pes1IFojJ_l">here</a></span></div>
<div style="text-align: justify;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen="" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/Vy5PLlpDoks/0.jpg" frameborder="0" height="266" src="https://www.youtube.com/embed/Vy5PLlpDoks?feature=player_embedded" width="320"></iframe></div>
<div style="text-align: justify;">
<b><u>Video from that playlist where I teach Graph Theory</u></b></div>
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Here is a short summary of important data structures and algorithms.<br />
<b>Basic Skill Set (BSS): </b><br />
1. Quick implementation & debugging (practise questions on codeforces, hackerrank, participate in contests)<br />
2. String Matching (important, KMP, Z-Algorithm, etc)<br />
3. <b>Binary Search</b>, Sorting, STL (sets, maps, unordered set/map, vector, sort) - very very very useful<br />
4. Data Structures - (Linked Lists, stacks, queues, BIT useful, Segment Tree - asked in Google)<br />
5. Dynamic Programming - very very important (medium level problems, all companies ask)<br />
6. Binary Trees & BST - super important! (All companies ask this)<br />
7. DFS/BFS questions on Graphs (Dijsktra and flows are rarely asked)<br />
8. DP on Trees (yes, an important topic)<br />
9. Greedy, Backtracking - (Important, can be tricky)<br />
10. Math Concepts like Prime Seive - Not that much important<br />
11. Bitmask DP - sometimes asked in interviews, cover it later.<br />
<br />
I think this is enough for cracking through most of the recruitment tests. Though there are always many other topics that can be covered, but I would suggest don't get overwhelmed and focus on these first. Once you are ready with these basics, you should move on to study other Data Structures and Algorithms. Knowing more and in detail will always make you more interesting and awesome.<br />
<br />
Many recruitment problems are based on usages of sets, maps.<br />
Do many practise problems based on them. Eg: <a href="http://codeforces.com/problemset/problem/567/D" target="_blank">see this</a>, and the <a href="http://codeforces.com/blog/entry/19604" target="_blank">solution</a>.<br />
<br />
<br />
<b>Tips for recruitment tests:</b><br />
1. Be fast. Don't just keep on waiting for finding the solution.<br />
2. If stuck on problem, proceed to next. First solve all of those that are easy.<br />
3. At the end, ALWAYS submit the worst brute force solution with no matter what complexity. YES! The test cases are many times weak, and you get pretty high score.<br />
4. You must be familiar with Python inbuilt functions involving combinatorics, permutations and string functionalities too. It can prove to be very beneficial ;)<br />
5. This tip is more of a personal experience. In one of the test, I was getting only a score of 25. I soon realized that the for loop conditions weren't true and I was simply printing 0. When I corrected it, I got a score of 75. Yes! so I had to basically see that if I am getting a WA in some test case, I need to print 0 there. Finally I used binary search on the values of variables(size of array, first element of array) to identify those test cases, and simply print 0. Basically what I did was used an infinite while loop with some condition like $100<n$ and $n<500$ so that I get the verdict TLE, and I am able to figure out those test cases where I was getting WA.<br />
<br />
<br />
<b>Tips for interviews:</b><br />
1. Be humble. Don't give the <b>slightest vibes </b>of overconfidence or arrogance.<br />
2. Never give up. If the problem asked seems difficult at first sight, don't lose out confidence. See what is given, what you have to find, and try doing it for small test cases. Then maybe you will find a pattern.<br />
3. Speak as you think. Don't just keep scribbling on paper. Let the interviewer know about how you are approaching the problem.<br />
4. If problem seems difficult, give the brute force solution and its complexity. Then try optimizing it, maybe using dynamic programming or some greedy solution.<br />
<br />
Don't think you don't have time :D<br />
Just start doing already!<br />
Feel free to write your queries, I am always there to help :)<br />
<br />
<br />
<b>Important Playlists:</b><br />
<b>================</b><br />
Famous Interview Questions You Must Know ►<a href="https://www.youtube.com/watch?v=u5-ss5kKy7g&list=PLfBJlB6T2eOshO8-LYaMt-Pes1IFojJ_l">click here</a><br />
Tips & Tricks for Success in Career ►<a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOv8klCHHNVLOmTOIxKu-xzn">click here</a><br />
How to Improve at Data Structures ► <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOup9gVZLAMjEV50YPKcPXuO">click here</a><br />
OOPS Interview Questions ► <a href="https://www.youtube.com/watch?v=qsMahidcehY&list=PLfBJlB6T2eOv0s4dZXm_uhOt5GmmfDs8-">click here</a><br />
Gaurav Challenges Rachit ► <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOvIEiSo43vr4vk7ASI4GkVS">click here</a><br />
How to use Codeforces for Improving ► <a href="https://www.youtube.com/watch?v=X-2OUqnUH6U&list=PLfBJlB6T2eOuDDm9xscqMZR3nnLP5FiyN">click here</a><br />
Math Problems with Interesting Analysis ► <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOthkt1Lkt839s8lcfcbQzJr">click here</a><br />
<ul style="text-align: left;">
</ul>
<br />
<br />
<b>Courses Taught by Me</b><br />
<b>==================</b><br />
Dynamic Programming: Zero to Hero ► click <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOtMXgK3FLUTawHjzpIEySHF">here</a><br />
Dynamic Programming on Trees ► <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOsET4tlfcLs7oXR7kCyt1xc">click here</a><br />
Graph Theory for Beginners ► <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOu3dTPKzvAf2axlmQUXGY91">click here</a><br />
SquareRoot Decomposition for Beginners ► <a href="https://www.youtube.com/watch?v=bvZ0TxZSGmk&list=PLfBJlB6T2eOvR8yXHkdju-jDpW2bD8Rlj">click here</a><br />
Segment Trees ► <a href="https://youtu.be/gNf5ZQsqr0w">click here</a><br />
<br />
<b>My Code Library</b><br />
<b>==============</b><br />
Github ► <a href="https://github.com/rachitiitr/DataStructures-Algorithms">https://github.com/rachitiitr/DataStructures-Algorithms</a><br />
<br />
<br />
<b>Follow me:</b><br />
<b>==========</b><br />
Instagram ►<a href="https://www.instagram.com/rachitjain2095">https://www.instagram.com/rachitjain2095</a><br />
LinkedIn ► <a href="https://www.linkedin.com/in/rachitiitr/">https://www.linkedin.com/in/rachitiitr/</a><br />
Facebook ►<a href="http://fb.me/AlgorithmsWithRachitJain"> http://fb.me/AlgorithmsWithRachitJain</a><br />
Programming Blog ► <a href="https://rachitiitr.blogspot.com/">https://rachitiitr.blogspot.com</a><br />
Twitter ►<a href="https://twitter.com/RachitJ55307787"> https://twitter.com/RachitJ55307787</a><br />
<br />
<br />
<b>Programming Profiles:</b><br />
<b>===================</b><br />
CodeForces ►<a href="http://www.codeforces.com/profile/rachitjain"> http://www.codeforces.com/profile/rachitjain</a><br />
CodeChef ► <a href="http://www.codechef.com/users/rachitiitr">http://www.codechef.com/users/rachitiitr</a></div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com5tag:blogger.com,1999:blog-9093889912215350229.post-22474493865055167942018-10-06T13:17:00.001+05:302019-12-27T17:36:22.979+05:30This is why you are FAILING at Interviews<div dir="ltr" style="text-align: left;" trbidi="on">
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Hi,</div>
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Here is another video from my side: <a href="https://www.youtube.com/watch?v=LK02ZPv9vdk" style="color: #3b5998; text-decoration-line: none;">"This is why you are failing at Coding Interviews"</a></div>
<div class="separator" style="clear: both; text-align: center;">
<iframe width="320" height="266" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/LK02ZPv9vdk/0.jpg" src="https://www.youtube.com/embed/LK02ZPv9vdk?feature=player_embedded" frameborder="0" allowfullscreen></iframe></div>
<div class="separator" style="background-color: #fefdfa; clear: both; color: #333333; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; text-align: center;">
<br /></div>
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
<br /></div>
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
If you have not <a href="https://youtube.com/c/RachitJain" style="color: #3b5998; text-decoration-line: none;">subscribed to my YouTube channel</a>, now is the right time as its all about making you ready to get your dream job. I share tips, lectures(like dp, dp on trees, graphs, squareroot decomposition), and the right mindset needed to crack coding interviews.</div>
<div style="background-color: white; border: none; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
<span style="color: #333333; font-family: Trebuchet MS;"><span style="font-size: 13px;">Rachit, an IIT Roorkee Alumnus and Software Engineer at Microsoft shares the major issues that people overlook while they are failing at Coding Interviews, despite being good at technical skills.</span></span></div>
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Subscribe to see more of me. Let me know if this helped. Go get a job at your dream company!</div>
<div style="background-color: white; border: none; color: #333333; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Cheers!</div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-3809497140185180682018-09-29T11:13:00.001+05:302018-09-29T11:13:12.727+05:30If you are preparing for Coding Interviews, WATCH THIS!<div dir="ltr" style="text-align: left;" trbidi="on">
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Hi,</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Here is another video from my side: <a href="https://goo.gl/UPbTWn" style="color: #3b5998; text-decoration-line: none;">"If you are preparing for Coding Interviews, WATCH THIS!"</a></div>
<div class="separator" style="clear: both; text-align: center;">
<iframe width="320" height="266" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/aqjy-XYmNi8/0.jpg" src="https://www.youtube.com/embed/aqjy-XYmNi8?feature=player_embedded" frameborder="0" allowfullscreen></iframe></div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
<br /></div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
If you have not <a href="https://youtube.com/c/RachitJain" style="color: #3b5998; text-decoration-line: none;">subscribed to my YouTube channel</a>, now is the right time as its all about making you ready to get your dream job. I share tips, lectures(like dp, dp on trees, graphs, squareroot decomposition), and the right mindset needed to crack coding interviews.</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
In this video, I share what is the story behind the present hiring process for companies like Microsoft, Amazon, Goldman Sachs and then I share what are the various topics you need to study to prepare for them.</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Subscribe to see more of me. Let me know if this helped. Go get a job at your dream company!</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Cheers!</div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com1tag:blogger.com,1999:blog-9093889912215350229.post-51039057889193275002018-04-07T19:12:00.000+05:302018-04-07T19:28:57.714+05:30How to excel at Competitive Programming | ft. FFAO from Codeforces<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "trebuchet ms" , sans-serif;">Hi guys! ✋</span><br />
<div style="display: none;">
rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
<div>
<br />
I got the opportunity to talk to one of my favorite coders. I remember I used to read comments by <b>ffao</b> and just see how great his rating curve is and how soon he came red on Codeforces.<br />
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<span style="font-family: "trebuchet ms" , sans-serif;">So I made a video on YouTube where <b>ffao</b> answered a lot many questions about competitive programming and how one can excel in this field.<br /><br />My screencast software got some issues and we got a poor video quality and I sincerely apologize to <b>ffao</b> and the audience.</span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">I can't ask <b>ffao</b> the time to again record with me, and I was almost sure of not uploading the video. But the audio is great, and I decided to have it on my YouTube channel. </span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;"><br /></span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">You can watch the video <a href="https://youtu.be/yXi891Jc-V4">here</a>.</span>
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<div style="text-align: center;">
<iframe allow="autoplay; encrypted-media" allowfullscreen="" frameborder="0" height="320" src="https://www.youtube.com/embed/yXi891Jc-V4?ecver=1" width="400"></iframe>
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<span style="font-family: "trebuchet ms" , sans-serif;">You can also refer this blog post to have a summary of what we discussed in the video.</span></div>
<ul style="text-align: left;">
<li>What's your educational background?</li>
<ul>
<li>ffao: I have a five-year bachelor’s degree in Computer Engineering from Instituto Tecnológico de Aeronáutica (ITA), a Brazilian university</li>
</ul>
</ul>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">When did you start programming?</span></span></span></span></li>
<ul>
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: </span></span></span></span>I wrote my first program when I was 13, as with a lot of people that happened because I really liked video games and wanted to know more about making them (spoiler: turns out it’s actually quite time-consuming). At that point I could only make very simple programs, like “type in a number and the program tells you if it’s even or not”, but I picked up more as I went along.</li>
</ul>
</ul>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">Why does math background help?</span></span></span></span></li>
<ul>
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: </span></span></span></span>I can’t even pinpoint where the math ends and the programming starts! Functions, recursive relations, geometry, transforming algebraic expressions – these are all things you do routinely in math and these are all things you do routinely in competitive programming. Just as math helped me with programming, studying for programming also helped me do better at math, so these things are quite tightly coupled.</li>
</ul>
</ul>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">Should students prefer math over computer science for graduation?</span></span></span></span></li>
<ul>
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: </span></span></span></span>There isn’t an objectively correct answer to this question – graduation choice should be influenced by the student’s tastes and what they intend to do with their life, so my best advice would be to research what graduates at each of these fields tend to do and go towards the one that has the choices that appeal to you the most. Getting into a programming job in general is easier with a computer science degree, but I have heard of jobs that hire mathematicians due to their usual analytical skills.</li>
</ul>
</ul>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">Can you relate your success in programming to your childhood?</span></span></span></span></li>
<ul>
<li style="margin: 0px;"><span style="font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: Sure, I believe everyone’s experiences in their whole life matter - I’ve always liked math, so I didn’t have trouble with those parts. I also did a bit of programming, so I did not have to struggle with learning what ifs and whiles do since I already struggled with it before.</span></span></li>
</ul>
</ul>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: #212121; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">How can intermediate coders excel and reach the next target?</span></span></span></span></li>
<ul>
<li style="margin: 0px;"><span style="font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: Just keep at it – do every competition you can, and you’ll struggle with a problem or two; those should be the problems a bit above your skill level so make sure you understand why you couldn’t solve the problem you couldn’t solve. Could you have approached the problem in a different way to get to the solution faster? Is there a technique you can generalize to solve a class of similar problems if they show up?</span></span></li>
</ul>
</ul>
<div>
<span style="font-family: "calibri" , sans-serif;"><br /></span></div>
<div style="border: 0px; font-size: 15px; font-stretch: inherit; line-height: inherit; margin: 14pt 0px; padding: 0px; vertical-align: baseline;">
<span style="color: black; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><b>Other Questions that students requested:</b></span></span></div>
<div style="font-size: 13px;">
<span style="font-family: "trebuchet ms" , sans-serif;"></span></div>
<ul style="text-align: left;">
<li style="margin: 0px;"><span style="color: black; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">How to understand hard and tough concepts easily for example FFT , centroid decomposition etc.</span></span></span></span></li>
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<li style="margin: 0px;"><span style="color: black; font-family: "calibri" , sans-serif;"><span style="border: 0px; font-family: inherit; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="border: 0px; font-family: inherit; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: </span></span></span><span style="font-family: inherit; font-style: inherit; font-weight: inherit;"><span style="border: 0px; font-family: inherit; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">This sounds like the wrong question to ask. To be honest, FFT/centroid are not that useful and I didn’t learn about them for a </span></span><span style="font-family: inherit; font-style: inherit; font-weight: inherit;"><span style="border: 0px; font-family: inherit; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><i>very</i></span></span><span style="font-family: inherit; font-style: inherit; font-weight: inherit;"><span style="border: 0px; font-family: inherit; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"> long time (I think I only knew about those things for a few months?) The best thing is to just go doing full competitions, without trying to learn specific techniques, until one of them comes up. But if you really want to know, my generic way to learn things when they do come up is: look up an explanation from someone who knows the subject well (there are a lot of bad tutorials, so you might have to search a lot to find a good one), try to do the most basic possible thing with the technique, then solve a few problems to see potential alternative ways to use it, then go back to solving random problems until it comes up naturally again.</span></span></li>
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</ul>
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<li style="margin: 0px;"><span style="color: black; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">How to select problems for practice? Ladders in A2OJ sort problems by tag and number of submissions which are not that great.</span></span></span></span></li>
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<li style="margin: 0px;"><span style="color: black; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">ffao: </span></span></span></span><span style="font-family: calibri, sans-serif; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">If you are training for a certain competition A, an obvious choice is to do previous editions of that competition for training. There are a lot of ICPC Regionals available online, also other competitions with quality problems like topcoder and codeforces. There isn’t a perfect answer to this and you’ll eventually find problems that are not helpful, the important thing is just to keep at it and eventually you’ll come across something interesting. I went to the Google Code Jam finals in 2014 and another finalist asked me how to find good problems, so I guess none of us really know. </span></span><span style="font-family: "segoe ui emoji" , sans-serif; font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">😊</span></span></li>
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<li style="margin: 0px;"><span style="color: black; font-family: "calibri" , sans-serif; font-size: x-small;"><span style="border: 0px; font-family: inherit; font-size: 11pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;"><span style="border: 0px; font-family: inherit; font-size: 12pt; font-stretch: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline;">Tackling DP and understanding the states to be defined and how this though process goes inside his head so rapidly.!</span></span></span></span></li>
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<li style="margin: 0px;"><span style="font-family: "calibri" , sans-serif;">What ffao said is exactly told in one of my videos to Introduction to Dynamic Programming that you can watch here.</span></li>
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<span style="font-family: "trebuchet ms" , sans-serif;"><span style="font-size: 13px;"><b>Dynamic Programming: How to think of states?</b></span></span></div>
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com6tag:blogger.com,1999:blog-9093889912215350229.post-12797816794787946622017-09-06T17:40:00.002+05:302017-09-06T17:40:52.614+05:30[Tutorial] SquareRoot Decomposition + Dynamic Programming in Competitive Programming<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "trebuchet ms" , sans-serif;">Hi guys! ✋</span><br />
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rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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You are going to learn how Square Root Decomposition and DP can be mixed to generate harder problems.<br />
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<span style="font-family: "trebuchet ms" , sans-serif;">This is an awesome math problem on Matrices. It is based on DP + Data Structures(Fenwick Tree/SquareRoot Decomposition). Its a counting problem from <a href="https://csacademy.com/contest/junior-challenge-2017-day-2/task/cntgigelmat/statement/">CSAcademy Junior Challenge 2017</a>.</span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">Problem Link is <a href="https://csacademy.com/contest/junior-challenge-2017-day-2/task/cntgigelmat/statement/">here</a>. </span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">You are given a matrix $M$ with $N,M( \le 2000)$ rows and columns, and you have to count the no of <b>special square submatrices</b>. A square matrix is <b>special </b>if it has all $1s$ on its borders and principal diagonal(top-left to bottom-right). The rest of the matrix can be filled with either $0s$ and $1s$. </span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">In beginning, the problem seems to be solvable using only DP, but the solution is simply mind-blowing, jaw-dropping and beautiful. </span></div>
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<span style="font-family: "trebuchet ms" , sans-serif;">The trick here is to iterate on diagonals which are $O(N+M)$ in number. Then for each diagonal, count the number of special square submatrices that lie on current diaognal i.e their principal diagonal lies on the current diagonal that we are iterating. </span></div>
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<span style="font-family: trebuchet ms, sans-serif;">Lets pick any two points on the diagonal that we are currently at. </span></div>
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<span style="font-family: trebuchet ms, sans-serif;">Using DP, we do some preprocessing. Then the question is transformed to given two arrays $L,R$, find the number of pairs $(i, j)$ such that following 3 conditions are met: </span></div>
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<span style="font-family: trebuchet ms, sans-serif;">1. $i\le j$ </span></div>
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<span style="font-family: trebuchet ms, sans-serif;">2. $L_j \le i$</span></div>
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<span style="font-family: trebuchet ms, sans-serif;">3. $R_i \ge j$ </span></div>
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<span style="font-family: trebuchet ms, sans-serif;">We iterate on $j$, and use square root decomposition to solve this problem :)</span></div>
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<span style="font-family: trebuchet ms, sans-serif;"><span style="font-size: 13px;">The video tutorial is divided into 2 parts: </span></span><br />
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<span style="font-family: trebuchet ms, sans-serif;"><span style="font-size: 13px;"><b>1. Part1: Approaching the problem and building our solution</b></span></span></div>
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<span style="font-family: trebuchet ms, sans-serif;"><span style="font-size: 13px;"><b>2. Part2: The Square Root Decomposition part</b></span></span></div>
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Refer the Video Description to find the links to problem link and other relevant information.</div>
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com1tag:blogger.com,1999:blog-9093889912215350229.post-92065281086884640572017-08-30T12:06:00.002+05:302017-08-30T12:07:03.185+05:30An Interesting Math + Data Structure Problem from Codeforces (Round #430)<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: "trebuchet ms" , sans-serif;">Hi guys! ✋</span><br />
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rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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<span style="font-family: "trebuchet ms" , sans-serif;">This is a data structure(TRIE) + math based problem from <a href="http://codeforces.com/contest/842">Codeforces Round #430</a>.</span><br />
<span style="font-family: "trebuchet ms" , sans-serif;">Problem Link is <a href="http://codeforces.com/contest/842/problem/D">here</a>. </span><br />
<span style="font-family: "trebuchet ms" , sans-serif;">You are given an array $A$ of size $N$, and you have to perform $M$ operations on it. </span><br />
<span style="font-family: "trebuchet ms" , sans-serif;">In each operation, you are given an integer $x$, and you perform XOR operation of every element of the array with $x$. Note that the array is updated after every operation and subsequent operations are performed on modified array. At end of every operation, you need to print the mex value of the updated array. </span><br />
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<span style="font-family: "trebuchet ms" , sans-serif;">NOTE: mex of a set $A$ is the least whole number ( $\ge 0$ ) which is not present in $A$. </span></div>
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Check out the following video where I've described the solution:<br />
<a href="https://www.youtube.com/watch?v=PKDQO8B0V3A">CodeForces Round 430 - Problem D Tutorial (Number Theory, Trie)</a><br />
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Refer the Video Description to find the links to source code and problem link.</div>
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If you liked my efforts, please hit the like button 👍, subscribe and share the videos among your college :D <br />
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Have a good day! 😆<br />
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-7322216407796767592017-08-29T10:55:00.001+05:302017-08-29T10:55:09.916+05:30An Interesting Number Theory Problem from CSAcademy(Round #43)<div dir="ltr" style="text-align: left;" trbidi="on">
<span style="font-family: "trebuchet ms" , sans-serif;">Hi guys! ✋</span><br />
<div style="display: none;">
rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
<div>
<br /></div>
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This is a greedy, math problem from CSAcademy Round #43.<br />
You are given two integers $N,K$ and you are required to print an array of $N$ distinct integers $<10^6$ such that there are exactly $K$ pairs $(a[i], a[j])$ with their gcd as $1$. <br />
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Check out the following video where I've described the solution:<br />
<a href="https://www.youtube.com/watch?v=3trTWCCakHg" target="_blank">CSAcademy Round 43 - Coprime Pairs Tutorial (Number Theory)</a><br />
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Refer the Video Description to find the links to source code and problem link.</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
The family 💓 has grown to 600+ subscribers and I thank you guys for the love and support :) <br />
<br />
If you liked my efforts, please hit the like button 👍, subscribe and share the videos among your college :D <br />
<br />
Have a good day! 😆<br />
<br />
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com1tag:blogger.com,1999:blog-9093889912215350229.post-69941673793923012542017-08-25T08:43:00.000+05:302017-08-25T08:43:05.821+05:30YouTube Playlist for Dynamic Programming<div dir="ltr" style="text-align: left;" trbidi="on">
<span style="font-family: Trebuchet MS, sans-serif;">Hi guys! ✋</span><br />
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<span style="font-family: Trebuchet MS, sans-serif;">I am happy to launch the <a href="https://www.youtube.com/playlist?list=PLfBJlB6T2eOtMXgK3FLUTawHjzpIEySHF" target="_blank">YouTube playlist for Dynamic Programming: From Zero to Hero</a>.</span> </div>
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I've put in a lot of my efforts this time, kept the video detailed so that a lot of people (beginners for sure) are able to understand:<br />
1. How to approach problems based on Dynamic Programming?<br />
2. How to think of DP states?<br />
3. How to build the DP recurrence relations?<br />
<b>4. Can DP problem be solved faster using MATRIX EXPONENTIATION? ✌</b><br />
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Beginners will surely learn a lot, lot, lot from this. </div>
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Check out the following videos:<br />
1. <a href="https://www.youtube.com/watch?v=tb_14w_-mNw" target="_blank">Intro to DP: How to approach DP states, Recurrences </a><br />
2. <a href="https://www.youtube.com/watch?v=TTtOpv6Hrcg&t=2s" target="_blank">Dynamic Programming + Matrix Exponentiation</a><br />
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Check the Video Description to find the links to source code and problem link.</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Finally, the family 💓 has grown to 500+ subscribers and I thank you guys for the love and support :) <br />
<br />
If you liked my efforts, please hit the like button 👍, subscribe and share the videos among your college :D <br />
<br />
Have a good day! 😆<br />
<br />
<br /></div>
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-58646972776848477602017-08-19T20:44:00.001+05:302017-08-19T20:44:16.775+05:30Video Tutorial For a SquareRoot Decomposition Problem - HILLJUMPING<div dir="ltr" style="text-align: left;" trbidi="on">
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rachit jain blog, Rachit Jain, rachit jain iit roorkee, rachit jain iitr, rachit iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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<span style="background-color: white; font-family: "trebuchet ms"; font-size: 13px;">Hi</span><br />
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I've put in a lot of my efforts this time, kept the video detailed so that a lot of people including beginners are able to understand how to solve this <strong>tough</strong> squareroot decomposition problem <a href="https://www.codechef.com/AUG17/problems/HILLJUMP" style="color: #578fb2; text-decoration-line: none;">HILLJUMPING</a> from Codechef August 17 Long Challenge. <br />
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You can learn about SquareRoot Decomposition, binary search, and how a simple and beautiful solution is built up, starting from scratch :D <br />
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Beginners will surely learn a lot, lot, lot from this. </div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
Check out the <a href="https://www.youtube.com/watch?v=7afjGOV18SI" style="color: #578fb2; text-decoration-line: none;">video editorial here</a>.<br />
Check the Video Description to find the links to source code and problem link.</div>
<div style="background-color: white; border: none; font-family: "Trebuchet MS"; font-size: 13px; line-height: 18.2px; margin-bottom: 13px; max-width: 700px; padding: 0px;">
If you do not want the problem description, skip to 3:25<br />
Then I explain my approach till 14:50 after which code discussion begins. <br />
<br />
Also, YouTube decreased the volume level after upload. So please use headfones, and if any of you<br />
has a solution to this, let me know!<br />
<br />
<br /></div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com5tag:blogger.com,1999:blog-9093889912215350229.post-61583417914655664762017-08-18T19:18:00.002+05:302017-08-19T20:40:02.505+05:30My YouTube Channel for Competitive Programming<div dir="ltr" style="text-align: left;" trbidi="on">
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</h2>
<b>My very own YouTube Channel</b><br />
<br />
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Tags: video-tutorials,YouTube,data-structures, algorithms<br />
<br />
Hi everybody, <br />
<br />
I've finally launched my very own <a href="https://www.youtube.com/channel/UC9fDC_eBh9e_bogw87DbGKQ?view_as=subscriber" target="_blank">YouTube Channel here</a>. <br />
<br />
<span style="color: red;"><span style="font-size: large;">Its a kind request to LIKE the video if it helped you.</span><b> </b></span><br />
<b><span style="color: red;">This is important for me as more likes builds a trust for future viewers :)</span></b><br />
<br />
At present, I plan to upload my video screencasts of online contests and video tutorials of some interesting programming problems that I encounter during daily online contests. <br />
<br />
The pattern each video follows is: <br />
1. Problem Description <br />
2. Explanation/Solution <br />
3. Code Implementation/Discussion <br />
<br />
<b>As a beginner, I was a bit slow while talking and I request all of you to watch the videos at 1.25x or 1.5x speed for better experience.</b><br />
<br />
To begin off, I've covered some problems from the [Codechef August Long Challenge](https://www.codechef.com/AUG17). <br />
<br />
1. <a href="https://www.codechef.com/AUG17/problems/PALINGAM" target="_blank">[Palindromic Game]</a> (Analysis based, medium) <br />
=> <a href="https://www.youtube.com/watch?v=6ppP76Bm9LY" target="_blank">Video Link </a><br />
<br />
2. <a href="https://www.codechef.com/AUG17/problems/CHEFFA" target="_blank">[Chef and Fibonacci Array]</a> (Medium DP)<br />
=> <a href="https://www.youtube.com/watch?v=qJPCONPbQ1U" target="_blank">Video Link </a><br />
<br />
3. <a href="https://www.codechef.com/AUG17/problems/STRINGRA" target="_blank">[Strings and Graphs]</a> (Interesting analysis, medium-hard) <br />
=> <a href="https://www.youtube.com/watch?v=xkJdvb8CGRk" target="_blank">Video Link</a><br />
<br />
<a href="https://www.youtube.com/watch?v=7afjGOV18SI" target="_blank">Video </a>for <a href="https://www.codechef.com/AUG17/problems/HILLJUMP" target="_blank">Hill Jumping</a> will be coming soon :) <br />
EDIT: Here is the <a href="https://www.youtube.com/watch?v=7afjGOV18SI" target="_blank">video editorial</a> for Hill Jumping.<br />
<br />
<b>Why should you subscribe to this channel:</b><br />
1. You couldn't solve problems I make videos about: majorly covers beginners and intermediate level coders. <br />
2. You face difficulty in understanding the text editorial. <br />
3. You enjoy solving difficult yet interesting problems. <br />
4. You really wanted some YouTube channel that talks about problems based on data structures and algorithms, and discuss how they can be solved. <br />
<br />
I hope this will help many people. Please subscribe and like the videos if you found them helpful. <br />
Comment if you face any difficulties or if you have any recommendations for me. <br />
<br />
With my common sense and your feedback, I hope the future videos will be of much greater quality :) <br />
<br />
Have a good day!<br />
<div>
<br /></div>
<br />
<br /></div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com11tag:blogger.com,1999:blog-9093889912215350229.post-65717771777068939402017-07-22T12:53:00.001+05:302018-09-29T10:29:48.471+05:30Tips for How to Prepare for Placement Interviews<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: placement, interviews, data-structures, algorithms<br />
<br />
Hi! Today I will write about some tips, tricks and hacks I have found from my experience in attempting recruitment tests, interviews. <br />
<br />
I will begin by giving a brief introduction about myself.<br />
I have done B. Tech. in <b>Electrical Engineering </b>from <b>IIT Roorkee.</b> I have graduated 2 months back, and now working in <b>Microsoft </b>for over a month<b>.</b><br />
<br />
I started off competitive programming in <b>2-2</b>(2nd Year 2nd Semester)<b>. </b>So I had around 1.5 years of experience in competitive programming while I was sitting for placement tests. Having a strong background in competitive programming really saves your ass while others keep reading geeksforgeeks to prepare themselves.<br />
<br />
<b><span style="font-size: large;">How to crack the interviews and get a decent job?</span></b><br />
So, the organizations will be coming in many colleges soon, and conduct their shortlisting tests.<br />
Now, I will be talking very short and to the point. Each point is important.<br />
<br />
<b>Basic Skill Set (BSS): </b><br />
1. Quick implementation & debugging (practise questions on codeforces, hackerrank, participate in contests)<br />
2. String Matching (important, KMP, Z-Algorithm, etc)<br />
3. <b>Binary Search</b>, Sorting, STL (sets, maps, unordered set/map, vector, sort) - very very very useful<br />
4. Data Structures - (Linked Lists, stacks, queues, BIT useful, Segment Tree - asked in Google)<br />
5. Dynamic Programming - very very important (medium level problems, all companies ask)<br />
6. Binary Trees & BST - super important! (All companies ask this)<br />
7. DFS/BFS questions on Graphs (Dijsktra and flows are rarely asked)<br />
8. DP on Trees (yes, an important topic)<br />
9. Greedy, Backtracking - (Important, can be tricky)<br />
10. Math Concepts like Prime Seive - Not that much important<br />
11. Bitmask DP - sometimes asked in interviews, cover it later.<br />
<br />
I think this is enough for cracking through most of the recruitment tests. Though there are always many other topics that can be covered, but I would suggest don't get overwhelmed and focus on these first. Once you are ready with these basics, you should move on to study other Data Structures and Algorithms. Knowing more and in detail will always make you more interesting and awesome.<br />
<br />
Many recruitment problems are based on usages of sets, maps.<br />
Do many practise problems based on them. Eg: <a href="http://codeforces.com/problemset/problem/567/D" target="_blank">see this</a>, and the <a href="http://codeforces.com/blog/entry/19604" target="_blank">solution</a>.<br />
<br />
<b>People who don't do CP should immediately do the following:</b><br />
1. Need to improve implementation, debugging skills.<br />
2. Learn the basic set of data structures and algorithms as mentioned above.<br />
3. Begin by doing all 37 problems on GeeksForGeeks under <a href="http://www.geeksforgeeks.org/array-data-structure/" target="_blank">array category</a>.<br />
4. Move on to DP on GeeksForGeeks.<br />
5. For sets, maps I think problems on CodeForces like I mentioned above will be better.<br />
6. Cover other topics like greedy, dfs/bfs from GeeksForGeeks.<br />
7. Linked list, binary trees and their traversals. (Important!)<br />
<br />
This should take around 2 weeks. I don't think people who are consistently doing CP would face the need of doing linked list, stacks, etc from geeksforgeeks. But its good if you give it a fast skimming read.<br />
<br />
<b>What next?</b><br />
Now start off at <a href="https://www.interviewbit.com/dashboard/" target="_blank">interviewbit </a>and solve problems there so that you familiarize yourself with verdicts like WA, AC, etc and also how to respond in case of TLE or WA. This will improve your implementation and debugging skills. This will clearly help you understand the various concepts like DP, trees, etc.<br />
<br />
You must also participate in the ongoing challenges on sites like Codechef, Codeforces, Hackerrank, etc.<br />
<br />
Once you are stable blue on CF around 1700, you can easily clear the recruitment tests. Then all you have to do is brush up your explanation skills so that you can clear the interview rounds too.<br />
<br />
<b>NOTE: </b>Speed is important. Many times people fail by 10-15 mins to implement the algorithm correctly. This will really turn you off. So keep practicing everyday!<br />
<br />
<b>Tips for recruitment tests:</b><br />
1. Be fast. Don't just keep on waiting for finding the solution.<br />
2. If stuck on problem, proceed to next. First solve all of those that are easy.<br />
3. At the end, ALWAYS submit the worst brute force solution with no matter what complexity. YES! The test cases are many times weak, and you get pretty high score.<br />
4. You must be familiar with Python inbuilt functions involving combinatorics, permutations and string functionalities too. It can prove to be very beneficial ;)<br />
5. This tip is more of a personal experience. In one of the test, I was getting only a score of 25. I soon realized that the for loop conditions weren't true and I was simply printing 0. When I corrected it, I got a score of 75. Yes! so I had to basically see that if I am getting a WA in some test case, I need to print 0 there. Finally I used binary search on the values of variables(size of array, first element of array) to identify those test cases, and simply print 0. Basically what I did was used an infinite while loop with some condition like $100<n$ and $n<500$ so that I get the verdict TLE, and I am able to figure out those test cases where I was getting WA.<br />
<br />
<br />
<b>Tips for interviews:</b><br />
1. Be humble. Don't give the <b>slightest vibes </b>of overconfidence or arrogance.<br />
2. Never give up. If the problem asked seems difficult at first sight, don't lose out confidence. See what is given, what you have to find, and try doing it for small test cases. Then maybe you will find a pattern.<br />
3. Speak as you think. Don't just keep scribbling on paper. Let the interviewer know about how you are approaching the problem.<br />
4. If problem seems difficult, give the brute force solution and its complexity. Then try optimizing it, maybe using dynamic programming or some greedy solution.<br />
<br />
Don't think you don't have time :D<br />
Just start doing already!<br />
Feel free to write your queries, I am always there to help :)</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com23tag:blogger.com,1999:blog-9093889912215350229.post-1231723357162245662017-06-30T00:06:00.001+05:302017-06-30T00:10:23.444+05:30An Interesting Problem On Array Conversion [AtCoder]<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: directed-graphs, hamiltonian paths..<br />
<br />
Today, I will talk about a <a href="http://agc016.contest.atcoder.jp/tasks/agc016_d" target="_blank">problem</a> from Atcoder<b>. </b><br />
You are given 2 arrays A,B. You need to tell the minimum no of moves to convert A into B. In each move, you replace any A[i] by the xor of all elements in A. If its not possible to convert A to B, print -1.<br />
<br />
Let us use 1-based indexing.<br />
Now, place xor(A) at position 0. Then the move is basically swapping numbers at position 0 and some arbitrary position i.<br />
So answer will only exist if both multisets of A, B (after including the xor of whole array) are same. <br />
<br />
You can refer to <a href="https://agc016.contest.atcoder.jp/editorial" target="_blank">editorial </a>given at AtCoder, but I find my approach a bit easier to understand, though they are more or less the same thing.<br />
<br />
So, in each move we swap a number $x$ at position $0$ with a number $y$ at position $i$. <br />
Let this be represented by a directed edge from $x$ to $y$. Then, in next move, we will swap $y$ with some $z$, then $z$ with blabla... and finally swap some blabla with $b[0]$. <br />
<br />
Isn't this a Hamiltonian Path from $a[0]$ to $b[0]$?<br />
<br />
Note that a directed edge from $x$ to $y$ means that the correct position of $x$ is actually the position of $y$ in $A$.<br />
$x→y$ means $x$ is at 0 position, and we place it at position of $y$, and bring $y$ to position $0$.<br />
So an edge represents putting $x$ into its correct position, and then bringing $y$ to position $0$ so that we can place it in its correct position, and so on.<br />
<br />
Consider an example,<br />
A: [1, 3, 2]<br />
B: [2, 1, 3]<br />
<br />
Now using the available move option of swapping any element with first element, we need to transform array $A$ into $B$.<br />
<br />
We perform 1→3 , $A$: [3,1,2] <br />
We perform 3→2, $A$: [2,1,3]<br />
<br />
You can see that the set of collection of edges denoting our operations are same as the set of collection of edges {b[i]→a[i] , 0 $\le i \le n$} <br />
This is because for given $a[0]$, and let its position in $B$ be $i$, then we basically swap the numbers at position $0$ and $i$. Thus, the edge $a[0]→a[i]$ is exactly represented by $b[i]→a[i]$. <br />
<br />
Now, $B$ is nothing but a permutation of $A$, and our edges are $b[i]→a[i]$. This is a standard thing that we often see in the world of competitive programming. The resultant graph is basically a forest of cycles. <br />
<br />
Now since we want a hamiltonian path from $a[0]$ to $b[0]$, we obviously need connectivity. For all cycles that aren't a part of $a[0]$ we will have to break down and re-edit their edges a little bit so that those cycles will also contain $a[0]$ as an element in it. <br />
<br />
If you didn't understand what I said above, try converting [1,3,2,7,8,9] to [2,1,3,9,7,8] by using move operation of swapping elements at position 0 and some arbitrary position $i$. <br />
<br />
In terms of math, let $C$ be a cycle that doesn't yet have $a[0]$ as a member in it. (For eg: in above example, $7→8→9→7$ is a cycle that doesn't include a[0] i.e 1). Pick two consecutive edges from $C$, $x→y$ and $y→z$. <br />
This means that when $x$ comes at pos $0$, we put it at position of $y$, <br />
and then put $y$ at position of $z$.<br />
Now see what happens when we swap $a[0]$ with $y$. Now $y$ comes at position $0$, and its destination position is still the position of $z$.<br />
But destination position of $x$ is now the position of $a[0]$ after swap as it took the place of $y$.<br />
And finally $a[0]$ has to come back to position $0$ , so destination position of $a[0]$ now becomes position of $y$. <br />
So the new edges are $x→a[0]$, $a[0]→y$ and $y→z$. So $a[0]$ is successfully inserted into the cycle $C$ at the cost of one additional edge. <br />
<br />
<b>NOTE:</b><br />
Bringing $a[0]$ into the cycle was necessary because our move operation allows us to swap any number with the number at position $0$. So once we get $a[0]$, we can apply the operation again and again i.e traverse the edges until the cycle is completed and all numbers are placed at their correct position. <br />
<br />
I hope this opens up your mind a bit. You now have the tools needed. I will recommend you to play around with it, consider a few examples, make the graphs, see how things are functioning.<br />
<br />
Finally here is the <a href="http://agc016.contest.atcoder.jp/submissions/1388409" target="_blank">AC code</a>.</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-29132030896485477252017-06-24T02:21:00.000+05:302017-06-24T02:37:50.911+05:30Introduction to a New Data Structure: WAVELET TREES<div dir="ltr" style="text-align: left;" trbidi="on">
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Wavelet Trees, Wavelet trees editorial, wavelet trees tutorial, wavelet tree rachit jain, Rachit Jain, rachit jain iit roorkee, rachit iitr, rachit jain iitr,rachit codechef, rachit hackerrank, rachit jain microsoft </div>
<span style="font-size: x-large;">Wavelet Trees</span><br />
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Tags: data-structures, wavelet-trees <br />
<br />
Today, I will talk about a new data structure: <b>Wavelet Trees. </b><br />
I read about them around a week back, and can't find the exact link where this was in discussion.<br />
<b><br /></b>
Anyway, you can read about it from this <a href="https://users.dcc.uchile.cl/~jperez/papers/ioiconf16.pdf" target="_blank">paper</a>. It's something really powerful, easy to code, and perhaps very new to competitive programming(I haven't heard about it in my experience of 2 years).<br />
<br />
Consider the following problems, and how I would have solved them normally:<br />
1. Number of elements in subarray $A[L...R]$ that are less than or equal to $y$. <br />
(Persistence Segment Tree?)<br />
2. Number of occurrences of element $x$ in subarray $A[L...R]$.<br />
(Subpart of 1st problem)<br />
3. The $k^{th}$ smallest element in subarray $A[L...R]$.<br />
(Ordered multiset + BIT would work for subarrays beginning from index 1)<br />
<br />
I know you might have many other solutions, and you might think what I am trying to prove.<br />
<br />
What if I told you, all of the above can be easily done in O(logn) using Wavelet Trees :o. Plus, its very easy to code :D Awesome, isn't it?<br />
<br />
I will be covering only range queries today that are mentioned above. There are some update queries too, that I might post in the coming posts. <br />
<br />
Okay, so I will be explaining what a wavelet tree is, and how we use it for finding the $k^{th}$ smallest number in any given subarray $A[L...R]$. <br />
<br />
<span style="font-size: large;"><b>TUTORIAL</b></span><br />
I will strongly recommend you to read section 2(around 4 pages) from the above paper. If really lazy, read just 2.5 pages beginning from section 2, and you will get a fair idea of what I am talking below.<br />
<br />
So wavelet trees are binary trees, where root node is represented by original array $A$ and the range $[lo, hi]$ in which the elements of array falls.<br />
Let $mid=(lo+hi)/2$<br />
Now, we partition(stable i.e the order of elements do not change) the array $A$ into two parts such that the left part contains all numbers that are $\le mid$, and right part contains all numbers that are $>mid$. <br />
This is something similar to what we do in quicksort. Isn't it?<br />
The range for left part becomes $[lo, mid]$ and for right part becomes $[mid+1, hi]$.<br />
<br />
We keep on doing this recursively for left and right parts, so the height of tree will be $O(log(max(A)))$. <br />
<br />
You can open the <a href="http://ideone.com/joqdYj" target="_blank">code </a>and refer it as you read all of this. <br />
<br />
So for every node $U$ of tree, we have the range $[lo, hi]$ in which its element lies and its array $S[U]$ represents a subsequence of original array.<br />
For every node $U$, we will have a vector $b$ such that $b[i]$ tells us the number of elements from first $i$ elements of $S[U]$ that are $\le mid$. i.e it represents how many elements from first $i$ elements will go to the left subtree of $U$.<br />
We can safely say that $(i-b[i])$ from first $i$ elements will go to right subtree.<br />
<br />
Now, the most awesome thing is that elements in subarray $[l, r]$ of $S[U]$ are exactly divided into the left and right subtrees of $U$ depending on whether the element is less than or greater than mid value. <br />
<br />
Okay, I will explain a bit more in detail.<br />
Let's consider the subarray of type $[1...R]$. <br />
Now $b[R]$ represents the number of elements that go to left subtree of $U$.<br />
The rest $(R-b[R])$ nos go to right subtree of $U$.<br />
So, we can query the present subarray $[1...R]$ by querying the starting $b[R]$ elements of left subtree and first $(R-b[R])$ elements of right subtree. <br />
<br />
When we want to do same thing on general subarrays $[L...R]$, we can see that $b[L-1]$ nos go to left subtree from first $(L-1)$ elements, and $b[R]$ nos go to left from first $R$ elements. This means that those elements in range $[L...R]$ that go to left are exactly represented by nos from position $(b[L-1]+1)$ to $b[R]$ in the left subtree.<br />
<br />
<span style="font-size: large;"><b>Kth Smallest Element in subarray [L...R]</b></span><br />
<div>
So, if the query is find Kth smallest element in subarray $[L...R]$, lets begin from the root.<br />
Now, $inLeft = (b[R] - b[L-1])$ gives the number of elements from subarray $[L...R]$ that go to left subtree. If this number is more than $K$, then we recursively go to left subtree. </div>
<div>
Otherwise, we go recursively to right subtree and find the $(K-inLeft)$ smallest element in that. </div>
<div>
Clearly, the complexity is the height of tree i.e $O(log(maxValue))$. </div>
<div>
<br /></div>
<div>
Refer this <a href="http://ideone.com/joqdYj" target="_blank">code </a>for understanding the implementation and explanation mentioned above.</div>
<div>
<br /></div>
<div>
Finally, this is the <a href="http://ideone.com/Tkters" target="_blank">complete code </a>that solves all the 3 queries mentioned above. </div>
<div>
<br /></div>
<div>
If you have any doubts, read the paper as mentioned (Section 2), and read the code for better understanding. If doubts still persist, write down below. </div>
<div>
<br /></div>
<div>
Note that there can be space issues with Wavelet Trees if array elements value are around $10^9$. You can avoid them by using coordinate compression. Another approach is to use Wavelet Matrix(Section 4.2) in above paper.</div>
<div>
<br /></div>
<div>
PS: I am really sleepy, and not sure if there are any bugs. I don't think there are but still its better if you test them by submitting on some related problem.</div>
<div>
<span style="font-weight: normal;"><br /></span></div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com11tag:blogger.com,1999:blog-9093889912215350229.post-69006447572921714442017-06-14T14:15:00.000+05:302017-06-14T14:15:47.376+05:30A Superb Problem on Hashing + Queries on Array [CodeChef]<div dir="ltr" style="text-align: left;" trbidi="on">
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Today, I will talk about <a href="https://www.codechef.com/JUNE17/problems/CLONEME" target="_blank">this</a> June Challenge Problem from Codechef. <br />
<br />
The beauty about the problem is the solution. I broke down the problem into subproblems, solved them, combined them. Though there exist multiple solutions, I think my solution is worth sharing. You can surely learn a lot of things from this ;) <br />
<br />
The problem is: you are given an array, and in each query you receive two subarrays. You need to tell whether these subarrays are almost similar. <br />
<br />
Two subarrays are almost similar if after you sort them both, there's atmost one mismatch.<br />
<br />
So how do I do this in O(logn) per query? Or maybe O(1) ?<br />
I was extremely puzzled how shall I carry this forward and build a solution.<br />
Using hashing, I can compute hash value of any subarray in O(1) using partial sums.<br />
But this only allows to compare whether two subarrays are IDENTICAL, and what we need is to allow a mismatch. <br />
<br />
If you do not understand any of the following, take time and think. It will be clear.<br />
<br />
So, here is what I did:<br />
1. Compute the hash values of both subarrays: $h1,h2$<br />
2. If they are equal, we are done.<br />
3. Otherwise, let $val = |h1-h2|$ and let $x,y$ be the mismatched elements in two subarrays.<br />
4. Then I computed xor of both subarrays. This gives us xor of $x$ and $y$.<br />
5. This can never be zero, so there's a bit set in this. Otherwise, print NO. Let the bit set be $k^{th}$ bit.<br />
6. I found the xor of both subarrays such that I only took those numbers into consideration whose $k^{th}$ bit is set. Let that be $v1,v2$ respectively.<br />
<br />
Now xor of $v1, v2$ will exactly give us that value of one of $x,y$. Think why this is true.<br />
For now, let's assume we get the value $x$.<br />
Then I check whether the resultant value ($x$)is present in a subarray or not. If it isn't present in any subarray, print NO.<br />
<br />
We can find the other variable i.e $y$. How?<br />
1. Let $hash[x]$ be the hashed value of numebr $x$.<br />
2. Then the hash sum of other elements that are common to both, $com=h1-hash[x]$.<br />
3. Then what is $tem=(h2-com)$? <br />
<br />
$tem$ is the hashed value of element $y$. So we check in reverse map to see the corresponding number, and finally get the value of $y$. If there is no number present in reverse map, print NO.<br />
<br />
<br />
Now we have successfully found the mismatch pair. But we must keep in mind that if we have come this far, this doesn't mean the answer exist. The subarrays still might NOT be almost similar.<br />
See this<br />
$A=\{1,3,5\}$ <br />
$B=\{1,5,6\}$<br />
The mismatch elements are $x=3,y=6$ as other elements are same. But once we sort them, their are more than 1 indices where a mismatch occurs. This is because the rank of mismatch pairs wasn't same.<br />
Now only thing left is to check if the rank of $x$ in first subarray and rank of $y$ in second subarray is same. For this I used a bit with nodes being an ordered multiset. <br />
<br />
I really felt so good after doing this.<br />
<br />
Finally the AC <a href="http://ideone.com/jPAHvd" target="_blank">code</a> for this problem is here.</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com14tag:blogger.com,1999:blog-9093889912215350229.post-26518254214337689742017-05-31T23:08:00.004+05:302017-05-31T23:11:55.807+05:30A Tricky DP Problem on Trees<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: small-to-large trick, dp, trees <br />
<br />
Not many programmers are aware of this "small-to-large" trick. I've picked up this <a href="https://csacademy.com/contest/round-31/task/uniform-trees/" target="_blank">problem</a> from CsAcademy Round 31: you are given a tree rooted at 1 where every node $i$ has some value, $val[i]$. You need to find the number of ways of selecting nodes so that the induced tree is uniform.<br />
1. A uniform tree is one where for every node, its direct child have same value. <br />
2. Induced tree from a subset of nodes $X$ is one where:<br />
a. There exists exactly one node that doesn't have any ancestor present in $X$.<br />
b. For every other node, its parent is its lowest ancestor that is present in $X$.<br />
<br />
The DP solution is as follows:<br />
Let dp[i][j] be the number of uniform forests(i.e it can be a single uniform tree, or a collection of uniform trees) that exist in the subtree of $i^{th}$ node such that the root of every tree in the forest has value $j$. <br />
Now $dp[i][j] = \left(\prod_{x\in child[i]}(dp[x][j]+1)\right)-1$ , if we do not include node $i$<br />
This is because from every child $x$, it can contribute forests with root value $j$ in $dp[x][j]$ ways, plus $1$ extra way, when we do not select any forest from $x^{th}$ child. <br />
So we need to subtract $-1$ from the total because we have also counted a way where all the children of node $i$ contribute no forest. <br />
<br />
Note that we can also include node $i$. This will add more ways in $dp[i][val[i]]$. <br />
<br />
If this is not clear, think more by drawing on paper. Also you can refer to <a href="https://csacademy.com/contest/round-31/task/uniform-trees/solution/" target="_blank">editorial</a> here.<br />
<br />
So this takes $O(n^2)$ time as well as space, and we need to do better.<br />
Note that for given subtree of node $i$, if none of the nodes in its subtree has $v$ value, then $dp[i][v]$ will be $0$. <br />
So we only iterate on the required values for given subtree using a map.<br />
<br />
Now here is the small-to-large technique part. When we are combining all the values for childs of node $i$, we can do that in a smarter way. We always iterate on the smaller sized map, and put its entries in the larger sized map. <br />
So whenever an item is being moved, it is always moved from smaller map to bigger map.<br />
This makes the size of resultant map greater than <b>twice </b>the size of smaller map. So each item can be moved upto max of $log_2(n)$ times, and we have $N$ items in total (one value per node). So we get $O(NlogN)$ time complexity as well as space. <br />
<br />
As usual, here is the <a href="http://ideone.com/hKjPww" target="_blank">code</a> implementing the above idea.<br />
<br />
I hope you've learnt a bit about this small-to-large technique. This is another <a href="http://codeforces.com/contest/600/problem/E" target="_blank">problem</a> based on it.<br />
You can compare my 2 solutions for the same: <a href="http://codeforces.com/contest/600/submission/20285389" target="_blank">based on Mo's</a>, <a href="http://codeforces.com/contest/600/submission/20287075" target="_blank">based on small-to-large</a>. See how shorter and cleaner the code becomes using this trick.<br />
<br />
Comment if you have any doubts. I'm always ready to help.<br />
<br />
<br /></div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com5tag:blogger.com,1999:blog-9093889912215350229.post-58894081898020515362017-05-30T00:19:00.005+05:302017-05-31T15:54:04.628+05:30A Hard Problem on Bit Logic<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: bits, analysis, math, counting problem <br />
<br />
This time, you will have a lot of fun. Get ready for some high level analysis! :D<br />
<br />
So this is some mind-boggling, extremely beautiful <a href="http://agc015.contest.atcoder.jp/tasks/agc015_d" target="_blank">problem</a> from AtCoder: you are having a collection of natural numbers from $L$ to $R(<10^{18})$ inclusive, you want to count the number of unique elements you can obtain by performing OR operation to the collection of your numbers. <br />
The approach I am mentioning below will not pass TL, but is something worth mentioning. <br />
<br />
I have solved a similar problem on CsAcademy, with the only difference being:<br />
1. We can use AND operation between the numbers from our collection. <br />
2. The collection of numbers was having no pattern, unlike here where we have nos from $L$ to $R$. <br />
<br />
<b>Approach 1(Slow)</b>:<br />
You might not understand this if you are unaware of <span style="color: blue;"><a href="http://codeforces.com/blog/entry/45223" target="_blank">SOS DP</a></span>. Also this solution will cause TLE.<br />
So you can SKIP this, otherwise you also learn one more technique.<br />
We can form a number $X$, only if $res = OR_i(a_i)$ is same as $X$, where $a_i$ is a number from our collection which is a subset of $X$ i.e $X\&a_i=a_i$. So if we perform OR operation on all such nos and the result is still not $X$, then unfortunately $X$ cannot be formed. <br />
This can be done in $O(A)$ or $O(Alg(A))$, where $A=max(a_1,a_2,...,a_n)$. <br />
How?<br />
Simple DP:<br />
Let dp[i][j] be the OR of all such elements that are subsets of $i$ and differ from $i$ in first $j$ bits.<br />
Then,<br />
if $j^{th}$ bit is set in $i$, $dp[i][j]=dp[i][j-1] | dp[i$^$(1<<j)][j-1]$<br />
otherwise $dp[i][j]=dp[i][j-1]$ <br />
<br />
This is commonly known as <a href="http://codeforces.com/blog/entry/45223" target="_blank">SOS DP</a>. If you didn't understand the above thing, see it from the link mentioned.<br />
Here is the code for <a href="http://ideone.com/uJQE7N" target="_blank">implementation</a> above.<br />
So this will not pass TL. We need to make use of the fact that in our problem we just don't have any numbers. We are given nos from $L$ to $R$. <br />
<br />
<b>Approach 2: </b><br />
The analysis is very beautiful and I really enjoyed solving this. <br />
Let $r$ be the 1st bit from left where $A,B$ differ. So we can remove the bits before this from both $A,B$ as they won't affect our answer because no matter what nos we select in OR operation those bits will remain as it is, and thus have just 1 choice. <br />
Now, $A<2^r\le B <2^{r+1}$ <br />
This equation is really very important as we will see later on. <br />
Let $T=2^r$, and lets partition the nos from $A$ to $B$ into 2 sets:<br />
$X=\{A,A+1,...,T-1\}$ and $Y=\{T,T+1,...,B\}$ <br />
<br />
<b>1.</b> <b>Taking nos from only X:</b><br />
We can obtain all nos from $A$ to $T-1$. That's it. We can't obtain higher nos as $T-1$ is already a bit sequence of all ones. <br />
<br />
<b>2.</b> <b>Taking nos from only Y:</b><br />
This is interesting.<br />
Note that $T\le B <2^{r+1}$, so $T,B$ have same number of bits.<br />
The highest bit set in both $T,B$ is $r$. Infact $T$ has only one bit set.<br />
Let the next highest bit set in $B$ be $k$. <br />
Now refer to the pic below. <br />
<br />
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsyaU4Xs4jrYWQQF5gfImqp7NxtaFarFBW4N13t75gD1_MvoalgK7v9FmsgudNPMC3nzVhFwSD8mQ2eeFR4nj3ZbqYSRd9S2kpEWMbXAOt8l4dD5QzvrB4uuGlVbZAqeYROUe_KMQuQQZc/s1600/IMG_20170529_233818.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="1100" data-original-width="1600" height="219" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsyaU4Xs4jrYWQQF5gfImqp7NxtaFarFBW4N13t75gD1_MvoalgK7v9FmsgudNPMC3nzVhFwSD8mQ2eeFR4nj3ZbqYSRd9S2kpEWMbXAOt8l4dD5QzvrB4uuGlVbZAqeYROUe_KMQuQQZc/s320/IMG_20170529_233818.jpg" width="320" /></a>We can trivially obtain all nos from $T$ to $B$. Point is how far can we go from $B$.<br />
Now refer to the image on left and read the following.<br />
The nos between $2^r$ and $2^r+2^k$ will be of form $1000*****$.<br />
The shaded portion of length $k-1$ bits will have all permutations of $0$s and $1$s(from $0$ to $2^k-1$).<br />
So we can set any pattern of $0$s and $1$s in the first $k-1$ bits of $B$ by suitable OR operations.<br />
This enables us to obtain any number from $B$ to $2^r+2^{k+1}-1$. Voila!<br />
<br />
So in this case, we can obtain nos from $T$ to $2^r + 2^{k+1}-1$. <br />
<br />
<b>3. Taking nos from X and Y:</b><br />
The min number thus obtained will be the OR of $A,T$ = $A+T=A+2^r$. <br />
Note that $T$ just has a bit set at $r^{th}$ position, while all nos from $X$ have bits from $0$ to $r-1$.<br />
$\therefore$, OR of $T=2^r$ with elements from $X$ will give us nos from $A+T$ to $T-1+T=2T-1$. <br />
Well, this is the highest number that we can achieve as it is $2^{r+1}-1$ i.e all bits set to $1$. So we can't go any further. <br />
<br />
Finally we have 3 segments, some of which may overlap. All that is left is to find the total length spanned by these segments. Phew!<br />
<br />
Here is the SMALL <a href="http://ideone.com/OMCaTU" target="_blank">code</a> implementing the above too BIG an idea.<br />
<br />
I loved this problem very much and had a lot of fun writing the explanation for it.<br />
Hope you have also learnt SOS DP trick incase you didn't know about it.<br />
Feel free to ask comment below incase of any queries.<br />
<br />
<br />
<b><br /></b>
<br />
<br /></div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com2tag:blogger.com,1999:blog-9093889912215350229.post-49913698600894751472017-05-29T15:21:00.001+05:302017-05-31T15:54:27.195+05:30A Connectivity Problem on Directed Graph<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: bitsets, graphs, SCC, connectivity<br />
<br />
So the Hackerrank <span style="color: blue;"><a href="https://www.hackerrank.com/contests/world-codesprint-11/challenges" target="_blank">Codesprint 11</a> </span>ended, and here is the <a href="https://www.hackerrank.com/contests/world-codesprint-11/challenges/hackerland" target="_blank">question</a> that I will talk about today: you are given a directed graph, and you will be given 2 types of queries: introduce a new node with an edge from/to the existing nodes, or answer whether there is a path from node $x_i$ to node $y_i$.<br />
<br />
If it were a undirected graph, DSU would have nailed it. <br />
Anyway, this is a standard technique used for connectivity in directed graphs. <br />
As for now, forget the type of query that modifies the graph structure. <br />
1. Find all the SCCs in the directed graph.<br />
2. Form a new graph, a DAG by compressing the SCCs and adding edges between the SCCs. <br />
3. Now for each SCC $A$, maintain the list$(reach[A])$ of all the SCCs it can reach. <br />
4. For given nodes $x$ and $y$, there is a path from $x$ to $y$ iff the SCC component $Y$ is present in $reach[X]$, where $X,Y$ refer to the SCC that contain $x,y$ respectively. <br />
<br />
Note that this takes $O(n^2)$ because of step $3$. We can do it faster by using <a href="https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwivkY-T6JTUAhXCu48KHQsUDGIQFggzMAA&url=http%3A%2F%2Fwww.geeksforgeeks.org%2Fc-bitset-and-its-application%2F&usg=AFQjCNG4E0jW1q7Ehb-R4dakDyVJnij2eg&sig2=b6cVbGzbnkzq5pI2dv5dzQ" target="_blank">BITSETS</a>. Click the above link which excellently outshows the applications of bitsets in C++. <br />
So we replace the list $reach[A]$ by the bitset $bit[A]$. <br />
<br />
So we now do this in $O(\frac{N^2}{32})$. This is pretty fast to pass the TL.<br />
<br />
Now notice that queries modifying the structure of graph won't affect our algorithm much.<br />
We first build the complete graph and then finally answer the queries. <br />
The only thing that one can worry about is that there might be some case for which the answer to present query is "No" but since we have built the complete graph, we might get a "Yes".<br />
So if answer for $x,y$ is "No", then this means that till now there isn't a path from $x$ to $y$. Notice that as we continue to modify the graph, we always bring a NEW node inside the structure and it's never possible in this way to add a path from $x$ to $y$. Wow!<br />
<br />
As usual, here is the <a href="http://ideone.com/Fmw7vR" target="_blank"><span style="color: blue;">code</span></a> implementing the above idea.<br />
I've seen similar questions in past hackerrank contest too(can't recall it).<br />
So I learnt that using bitsets is a standard technique for connectivity queries on directed graphs.<br />
<br /></div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com9tag:blogger.com,1999:blog-9093889912215350229.post-33779596788571334602017-05-29T02:11:00.002+05:302017-05-31T15:54:37.546+05:30A Hard Combinatorics Problem<div dir="ltr" style="text-align: left;" trbidi="on">
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Tags: math, combinatorics, DSU<br />
<br />
Now, this is a really beautiful <a href="http://agc012.contest.atcoder.jp/tasks/agc012_d" target="_blank"><span style="color: blue;">problem</span></a> from AtCoder: you are given an array of $N$ balls and two numbers $X,Y$. $col[i], w[i]$ represent the color and weight of $i^{th}$ ball respectively. You can swap two balls,$i$ and $j$ of same color if $w[i]+w[j] \le X$; you can swap two balls,$i$ and $j$ of different color if $w[i]+w[j] \le Y$. You need to find the total number of distinct permutations of colors that you can obtain. <br />
<br />
The solution is as follows:<br />
The key concept is that if you can swap balls $A,B$ and balls $B,C$, then you can also swap $A,C$ regardless of the condition. Why? <br />
1. Let the original position be $A ... B ... C$ <br />
2. Swap $A,B$ to obtain $B ... A ... C$ <br />
3. Swap $B,C$ to obtain $C ... A ... B$ <br />
4. Swap $A,B$ to obtain $C ... B ... A$ <br />
<div>
Voila! You can simply swap $A,C$. </div>
<div>
<br /></div>
<div>
This means that we need to make clusters of balls. A cluster contains balls that can be swapped into each other's position and the total answer would be the product of total permutations for each cluster of balls. </div>
<div>
<br /></div>
<div>
So the only problem is to make clusters. Each ball can be connected to $n-1$ other balls. So we have around $O(n^2)$ edges that we need to see and add. We need something faster.<br />
<br />
Note that each edge can be of two types, connecting balls of: same color or different color. We use DSU to add edges between the balls. </div>
<div>
1. If for every color $C$, we connect the lightest ball of color $C$ to all the balls of same color which can be joined as per the rules, we completely incorporate all the edges of type that connect two balls of same color. </div>
<div>
2. Now we find the two balls of different colors and minimum weight: let them be A,B.</div>
<div>
3. Connect all the balls of color different from $col[A]$ to $A$ if we can connect them. </div>
<div>
4. Now connect balls with color same as $col[A]$ to $B$ if we can connect them. </div>
<div>
<br /></div>
<div>
Each step takes $O(n)$ time. <br />
<br />
How this works? <br />
Consider $i^{th}, j^{th}$ balls, and assume that they can be swapped. We will prove that our idea of addng edges will already collect both these balls in the same cluster. <br />
<b>Case 1:</b> Same Color<br />
Let the lightest ball of that color be $k$.<br />
Since they can be swapped, <br />
$w[i]+w[j]\le X$<br />
This means that $w[i]+w[k] \le X, w[j]+w[k] \le X$ <br />
$\therefore $ our idea of connecting ball to the lightest ball of that color makes the cluster complete and we never miss out any edge of this type. <br />
<b>Case 2: </b>Different Color <br />
You can work(similar to what we did above) out to see that if $w[i]+w[j] \le Y$, then our idea would also collect both these balls in the same cluster.<br />
<br /></div>
<div>
Now we have made clusters, all that is left is to compute answers for each and then multiply them. </div>
<div>
Check the <a href="http://ideone.com/OPD2Fr" target="_blank"><span style="color: blue;">code</span></a> for implementation of above idea. </div>
<div>
<br /></div>
<div>
Overall, I had too much fun solving this problem and I learnt something from it.<br />
<br /></div>
</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com5tag:blogger.com,1999:blog-9093889912215350229.post-90477323102924866512017-05-29T01:52:00.000+05:302017-05-31T15:55:33.999+05:30A Longest SubArray Problem<div dir="ltr" style="text-align: left;" trbidi="on">
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Rachit Jain, rachit iit roorkee, rachit iitr, rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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Tags: data structures, constructive, math<br />
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Here is another interesting problem that I found as a subproblem while solving a difficult problem: you are given an array $A$, and you have to build up array $inc$ such that $inc[i]$ represents the length of longest good subarray(LGD) starting from $i$. We call a subarray $(L, R)$ good if its first element($A_L$) $\ge 1$, its second element($A_{L+1}$) is $\ge 2$, ...., its last element is $\ge (R-L+1)$. <br />
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Eg: If the array given is $A = \{1,2,3,3,3\}$ ,<br />
then the output will be $inc = \{3, 3, 3, 2, 1\}$. <br />
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Eg: If the array given is $A = \{4,2,3,5,9\}$ ,<br />
then the output will be $inc = \{5, 4, 3, 2, 1\}$. <br />
<br />
After a lot of thinking for about an hour, I had the following simple O(n) solution: <br />
<br />
Let $LGS_i$ mean the longest good subarray starting from index $i$. <br />
Let's modify our array $A$ as $A[i] = A[i] - i$, then: <br />
1. $LGS_0$ will continue to stretch till the maximum index $j$ such that $A[k]\ge 1$ for $k \le j$. <br />
2. $LGS_1$ will continue to stretch till the maximum index $j$ such that $A[k]\ge 0$ for $k \le j$. <br />
3. $LGS_2$ will continue to stretch till the maximum index $j$ such that $A[k]\ge -1$ for $k \le j$. <br />
<br />
Since at every step, the lower bound is always decreasing by 1, we can use one pointer to find the farthest ending point of good subarrays for all indices in $O(n)$. Note that we are able to use 1 pointer technique because of the fact that ending point of $LGS_i$ will always be after the ending point of $LGS_{i-1}$.<br />
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Check the <a href="http://ideone.com/DkXR6O" target="_blank">code</a> for the implementation of above idea.<br />
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-58340839132692924832017-05-26T16:12:00.000+05:302017-05-31T15:55:47.563+05:30A Greedy, Math Problem <div dir="ltr" style="text-align: left;" trbidi="on">
<div style="display:none"> Rachit Jain, rachit iit roorkee, rachit iitr, rachit codechef, rachit hackerrank, rachit jain microsoft </div>
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Tags: math, greedy, constructive, combinatorics</div>
So I have found questions from AtCoder interesting since the launch of the site. <head>
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Here is another <a href="http://agc012.contest.atcoder.jp/tasks/agc012_c" target="_blank"><span style="color: blue;">problem</span></a>: you are given a number $n(<10^{12})$ and you have to find an array of size $\le 200$, such that there exist exactly $n$ subsequences of the array which are good. A subsequence is good if it's first half is same as the second half like (1,2,3,1,2,3). </div>
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I was amazed by looking at the solution for this. I wasn't able to solve it on my own. So here is the solution: </div>
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Let $P_k$ denote any permutation of first $k$ natural nos. Then consider the array $A$ formed by adding the sequence of first $k$ natural nos to $P_k$ i.e $A$ = $\{P_k, 1, 2,3,4,...,k\}$ </div>
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Now the total no of good subsequences of $A$ is same as number of increasing subsequences in $P_k$. </div>
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Now, note that if total no of good subsequences in $P_k$ are $x$, then we can place the next number $k+1$ in </div>
1. Front of $P_k$, resulting in total good subsequences to be $x+1$. <br />
2. Back of $P_k$, resulting in total good subsequences to be $2x$. <br />
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Now when we need $n$ total good subsequences, we can recursively find the array that will generate it based on the parity of $n$. Note that you scale down $n$ by half in atmost two steps, so we will need at max $2log_2(10^{12})$ steps i.e $80$ steps.</div>
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Check the <a href="http://ideone.com/BiVjCG" target="_blank"><span style="color: blue;">code</span></a> for details. </div>
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-32711484601586967782016-12-20T23:22:00.003+05:302016-12-20T23:28:02.587+05:30Some life principles for a Happy Life<div dir="ltr" style="text-align: left;" trbidi="on">
This blog post is just to inspire people about life and saying goodbye to worries.<br />
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We all have aims and goals in our lives. There is a necessity for them. For example, I cannot live a life with no goals and watch tv series, sleep 10 hours a day. Though this looks fine for a day, 3 days, a week, enough! But this makes me carry unnecessary burden on my mind. Also due to lack of social circle, many people fall under depression and live life in despair.<br />
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In today's life, we worry way too much. But in reality that worry is not the worth. Constantly worrying causes depression, irritation, frustration, and bad mental health. I have adapted to the following 3 steps to stay away from these:<br />
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Step 1: Think about the worst possible outcome of the present situation.<br />
Step 2: Accept it.<br />
Step 3: See the possible actions you can do to make the outcomes less unfavorable.<br />
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On one side there is Napolean Bonaparte who had fame, power and money but couldn't recollect even six happy days of his life. On the other hand we have Hellen Keller, who was dumb and deaf but described life as the most beautiful thing.<br />
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We must keep ourselves engaged in some activities. Keep yourself busy. Just make sure that they are productive, require focus and enhance your creativity. For people who aren't that fond of reading(Look who's talking), they must give it a shot! Its worth it. Their have been 1000s of generations that have passed and have left their experiences. Its very good to read about random stuff daily.<br />
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This was what I learnt from my mother this December. She was noticing my behavior and finally made me realized where I was going wrong. I will definitely try to live by this and make my life much much stress-free. Following is the video she whatsapped me.<br />
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<iframe allowfullscreen="" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/x56_Kn2nULg/0.jpg" frameborder="0" height="266" src="https://www.youtube.com/embed/x56_Kn2nULg?feature=player_embedded" width="320"></iframe><br />
<b>Pro Tip: </b>We must remember the people who are close to us and make us happy. I feel thankful to my parents and close ones for being my moral support and feel blessed to have a perfectly complete life. :) No matter in how much trouble I am, there are people who will stand besides me. Trust is the most beautiful thing after love. Give it to people and never break it.<br />
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com1tag:blogger.com,1999:blog-9093889912215350229.post-83048406206646103132016-12-15T23:13:00.002+05:302016-12-15T23:13:59.933+05:30Removing "Hover to Expand Ads" using JavaScript<div dir="ltr" style="text-align: left;" trbidi="on">
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiaNvI9YZXodNKzWc6r4qZ7WWgPlLgCo_BwPkcTNtkPsrkPgLHl_EfLn29YBiC0lBQLjxwECXg0g3ooi291POCaexMYn9lwdCo5W9jc9_YXIZ5EzswIHupeJoeLBzQS5sN0W9czb0eD_dOl/s1600/expandad.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="39" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiaNvI9YZXodNKzWc6r4qZ7WWgPlLgCo_BwPkcTNtkPsrkPgLHl_EfLn29YBiC0lBQLjxwECXg0g3ooi291POCaexMYn9lwdCo5W9jc9_YXIZ5EzswIHupeJoeLBzQS5sN0W9czb0eD_dOl/s320/expandad.png" width="320" /></a></div>
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I am sure most of us have seen this irritating "Hover To Expan Ads". They were even displayed on ideone some time ago. I spent a few minutes to get over with this irritating stuff. Just paste the below code in the URL. Note that as you paste the link, "javascript:" gets removed. So type it again in the beginning and press enter.</div>
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<script src="https://gist.github.com/anonymous/097f085632dc1a0fb8e1d1471d763a98.js"></script>
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You can save the pain to copy paste this again and again simply by creating a bookmarklet with above code. Then all you need to do is click on the bookmarklet. Bookmarklets are nothing but the JS code that runs when you click on it.
See <a href="https://crossbrowsertesting.com/faq/how-do-i-install-bookmarklet-google-chrome-mac-os">this</a> to add a bookmarklet.</div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-29189089761573130002016-12-15T22:35:00.001+05:302016-12-15T22:54:10.031+05:30Binary Heaps in C++
<b>Pre-Requisites: </b>What are binary heaps?<br />
See <a href="http://quiz.geeksforgeeks.org/binary-heap/" target="_blank">here</a>.<br />
<br />
I personally found the implementation given in the above GeeksForGeeks link very long.<br />
The aim of this post is simply to provide a short and efficient implementation of min and max heap in C++.<br />
This helps me to revise just before the placement interviews too. :P<br />
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<b>Advantage:</b><br />
<b>1. </b>Short and efficient code.<br />
<b>2. </b>Works as both max-heap as well as min-heap.<br />
<br />
<a href="http://ideone.com/m1IfEB" target="_blank">Here</a> is the link of code at ideone.<br />
<br />
<script src="https://gist.github.com/anonymous/1b4c1fd8c929346bd10b22d5a8ee7981.js"></script>
<div style="display:none"> #include <bits/stdc++.h>
using namespace std;
class heap{
vector<int> a;
int order;
#define l(x) 2*x+1
#define r(x) 2*x+2
#define p(x) (x-1)/2
#define null -INT_MAX
public:
heap(int x = 0){ order = x; }
bool cmp(int x, int y){
if (order == 0) return x>y; //min-heap
if (order == 1) return x<y; //max-heap
}
void add(int x){
a.push_back(x);
go(a.size()-1);
}
void go(int u){
if(u == 0) return;
int P = p(u);
if(cmp(a[P], a[u])) swap(a[P], a[u]), go(P);
}
void heapify(int u){
int L = l(u), R = r(u), n = a.size();
if(L>=n and R>=n) return;
int v = (L<n&&R<n)?(cmp(a[R], a[L])?L:R):L;
if(cmp(a[u], a[v])) swap(a[u], a[v]), heapify(v);
}
int extract(){
if (a.empty()){
cout << "Oops! heap is empty!" << endl;
return null;
}
int ans = a[0];
if(a.size() == 1) {
a.clear();
return ans;
}
a[0] = a.back();
a.pop_back();
heapify(0);
return ans;
}
};
int main()
{
ios_base::sync_with_stdio(false);
cin.tie(NULL);
int i,n,k,j;
heap H(1); // 1 for max-heap, 0 for min-heap
vector<int> a{13, 1, 10, 34, 42, -10};
for(int x: a) H.add(x);
for(int x: a) cout << H.extract() << " ";
return 0;
} </div>
Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0tag:blogger.com,1999:blog-9093889912215350229.post-9146295034544351162016-12-09T15:01:00.003+05:302016-12-22T12:27:19.227+05:30Solving Linear Congruences $a*x \equiv b\ (\textrm{mod}\ n)$<div dir="ltr" style="text-align: left;" trbidi="on">
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<b>Note:</b> $(x,y)$ means $gcd(x, y)$ <br />
<b>Given:</b> $a,b,n$ and $(a,n)=1$ <br />
<b>To find:</b> $x$ such that $a*x \equiv b\ (\textrm{mod}\ n)$<br />
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<a href="https://www.youtube.com/watch?annotation_id=annotation_768190147&feature=iv&src_vid=ru7mWZJlRQg&v=mgvA3z-vOzc" target="_blank">This video</a> explains how to solve this problem using extended gcd method.<br />
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<b>Solution</b>:<br />
$\because (a, n) = 1$<br />
$\therefore$ $1=M*a+N*n$ for some integers $M, N$.<br />
Taking modulo $n$ on both sides,<br />
$a*M\equiv 1\ (\textrm{mod}\ n)$<br />
Simply multiply by $b$ on both sides,<br />
<br />
$a*M*b\equiv b\ (\textrm{mod}\ n)$<br />
$\therefore x=M*b$<br />
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Now problem is how to find $M,N$. We can use the <a href="https://www.youtube.com/watch?annotation_id=annotation_768190147&feature=iv&src_vid=ru7mWZJlRQg&v=mgvA3z-vOzc">Extended GCD Method</a> as explained in the link. Following is the C++ implementation for the same.<br />
<script src="https://gist.github.com/anonymous/35b737814b10a1e07c6d3e7d4b18594b.js"></script>
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<b>Problem to practise</b>: <a href="https://projecteuler.net/problem=134" target="_blank">Prime Connection</a><br />
<b>Solution? </b><a href="http://ideone.com/p54ZJg" target="_blank">Click here</a><br />
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Rachit Jainhttp://www.blogger.com/profile/02906400765901317364noreply@blogger.com0