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Archives for November 2016

Review: How to Win Coding Competitions by ITMO University

By Duncan Smith Leave a Comment Nov 30 2

ITMO

Last month, ITMO University launched an edX course called How to Win Coding Competitions: Secrets of Champions. With this first iteration of the course coming to an end, I thought I would discuss my experience with it.

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An Ultralearning Approach to Competitive Programming Practice

By Duncan Smith Leave a Comment Nov 23 0

Studying

Scott Young has recently been writing about a concept he calls ultralearning, a philosophy and collection of techniques for quickly gaining mastery of a subject. This week, I’m going to explore how we can use ultralearning techniques for competitive programming practice.

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How Many Problems Do You Need to Solve?

By Duncan Smith Leave a Comment Nov 16 0

HowManyProblems

Programmers get better at competitive programming mainly by solving competitive programming problems. It’s true that there are other activities that go along with problem-solving practice. Reading about algorithms, data structures, and problem-solving techniques is useful to avoid re-inventing the wheel. And it’s even more important to read solutions after you solve a problem, so you can learn from other practitioners and fix your mistakes. But the core of the learning process is solving problems. Without that core, reading textbooks and solutions won’t get you very far.

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Review: Awesome Competitive Programming by Jasmine Chen

By Duncan Smith Leave a Comment Nov 9 0

Awesome

In January of this year, Jasmine Chen (lnishan) published a Codeforces blog post called An awesome list for competitive programming! Since then, she and a few collaborators have been editing and expanding the list on GitHub.

Awesome list in this context doesn’t just mean “a really great list.” It refers to a project started by Sindre Sorhus in which people create lists of links to useful and/or interesting resources, and publish them on GitHub. There is of course a list of these lists.

Here’s what the Awesome Competitive Programming list offers.

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How Long Should You Spend on a Problem?

By Duncan Smith Leave a Comment Nov 2 0

Hourglass

To get better at programming or math, it’s not enough to read about a topic. You have to solve problems. And solving problems is a lot more beneficial if you have access to solutions, especially ones with detailed explanations. But as useful as solutions are, they also present another problem: when is the best time to look at them?

Solving a problem yourself improves your understanding of a concept more than reading someone else’s solution. If that wasn’t true, then it would be possible to learn a technical subject just by reading about it. That would be easier, but it doesn’t work. So you need to struggle with problems.

However, you can’t avoid looking at the solution forever. Problems in textbooks or online judges are intended to be solved in hours or days. They aren’t unsolved research problems that take months or years to solve. (Or if they are, they’re clearly marked as such — e.g., some of the problems in Knuth’s books).

So part of your job as a problem-solver is to settle on the best time to look at each solution.

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Getting Started

Are you new here? Check out my review posts for a tour of the archives:

  • Lessons from the 2020 LeetCode Monthly Challenges
  • 2019 in Review
  • Competitive Programming Frequently Asked Questions: 2018 In Review
  • What I Learned Working On Time Tortoise in 2017
  • 2016 in Review
  • 2015 in Review
  • 2015 Summer Review

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