https://blog.rkempe.ca/series/why-does-theory-matter-in-computer-science/ Recent content in Why Does Theory Matter in Computer Science? on rkempe’s blog Hugo en-ca © Copyright 2026 Rebecca Kempe Fri, 20 Jun 2025 20:53:01 -0400 https://blog.rkempe.ca/posts/2025/06/why-does-theory-matter-in-computer-science-meta-commentary/ Fri, 20 Jun 2025 20:53:01 -0400 https://blog.rkempe.ca/posts/2025/06/why-does-theory-matter-in-computer-science-meta-commentary/ When I first started doing this writeup, I did not expect to still be working on it 6 months later. Finishing this was a long, long overdue task for a while. This is the second write-up I’ve done of a talk I’ve given. The first one I did was for “How to be a Talentless Hack in Public”, which I published in zine form first, before then publishing the text on this blog several months later. https://blog.rkempe.ca/posts/2025/05/why-does-theory-matter-in-computer-science-part-5/ Thu, 22 May 2025 21:34:31 -0400 https://blog.rkempe.ca/posts/2025/05/why-does-theory-matter-in-computer-science-part-5/ Here is a long list of sources I consulted at various points while doing research for this project. As it might have become clear through reading the previous installments of this series, this was more a talk about the densest subgraph problem than it was about theory being useful in computer science. There are a few reasons for that, which I might explain in more detail at some point in the future. This means that I presented a lot of information that I borrowed from other people! Here’s an annotated bibliography of sorts, in case you were interested in going deeper, for whatever reason. https://blog.rkempe.ca/posts/2025/05/why-does-theory-matter-in-computer-science-part-4/ Thu, 22 May 2025 21:28:43 -0400 https://blog.rkempe.ca/posts/2025/05/why-does-theory-matter-in-computer-science-part-4/ In Part 3, we discussed the densest subgraph problem (DSP) and some algorithms for solving it. In this section, we’ll be looking at how we can generalize this problem and those algorithms to solve some other problems. This is the part of the talk where I will introduce some fancy new math I had to learn in order to understand how one might generalize iterative peeling to solve adjacent problems. https://blog.rkempe.ca/posts/2025/02/why-does-theory-matter-in-computer-science-part-3/ Thu, 13 Feb 2025 23:17:01 -0500 https://blog.rkempe.ca/posts/2025/02/why-does-theory-matter-in-computer-science-part-3/ In Part 2 of this talk, we gave a crash course to graph theory and showed how we can use it to view some real-world problems as instances of the densest subgraph problem (DSP). But what exactly is the DSP? If you’ve studied graph theory, you may have heard of something called the Maximum Clique Problem. The goal of the max clique problem is to find the largest complete subgraph in a graph. If we consider our vertices to be people, and edges to represent a friendship relationship between two people, in the max clique problem we are trying to find the largest friend group in a community. https://blog.rkempe.ca/posts/2025/01/why-does-theory-matter-in-computer-science-part-2/ Fri, 24 Jan 2025 12:47:46 -0500 https://blog.rkempe.ca/posts/2025/01/why-does-theory-matter-in-computer-science-part-2/ In the first part of this talk, I made the case that theory is useful because it allows us to find (or at the very least, have the correct toolkit and language to explore) solutions to real-world problems. In this part, we are going to look at some examples of such problems and develop mathematical language to be able to discuss them more abstractly. I’ve put the term “real-world” in quotes in the title, because I’m going to be talking about these problems in a lot of generality. However, I want to stress that specific instances of these problems are actually relevant in industry, and I think it’ll be easy to see why once I start talking about them. https://blog.rkempe.ca/posts/2024/12/why-does-theory-matter-in-computer-science-part-1/ Sun, 29 Dec 2024 00:38:01 -0500 https://blog.rkempe.ca/posts/2024/12/why-does-theory-matter-in-computer-science-part-1/ If you’re a computer science student, you probably had to take an introductory discrete math course at some point. Did you enjoy it? If so, this talk probably isn’t for you, so you can feel free to skip the rest. (Or not – hopefully you feel like you can still learn something from me!) Jokes aside, it’s actually okay not to enjoy your intro to discrete math course: like, personally, I loved mine, but I also completely hated my discrete probability course and would prefer never to see it again. But I pick on discrete math because I feel like if it’s taught well, it can be a turning point for many people, and it certainly was for me.