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.
Archives for November 2016
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.
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.
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.