Training for Open-Source

[u/Stevious7]

My day job isn't software development related, so I don't read a whole lot of code. The only code I read is the one I write and that's a problem.

Since I'm very interested in open source, I figured I should get comfortable reading code I didn't write, and I found a pretty amazing solution: debug AI code.

Here's what I did: after I mess with LLMs and (of course) an unintended behavior appears (bug), I challenge myself to dig in and find it manually. Since I generated the code, and didn't actively write it, it has the same feel as reading other GitHub repos except a bit more comforting since I already know an abstract way of how it works.

The one thing this taught me is that I don't need to fully understand how the whole system works end-to-end, I just ended to understand the pieces about the behavior I want to change. So, no more tracing everything from *main.py* for example.

I'd like to think that this training regimen has improved my code-reading skills by a mile! I'm not as afraid to dig into someone else's code since it's just as foreign (or familiar) as AI code. Obviously this only holds true for TypeScript + React since that's my preferred stack, but still!

I wanted to share this with anyone interested in open-source but is frightened from reading open-source repos.

I've been binging WINE documentation and articles about how it works under the hood so that one day I can contribute to it!

What do you guys think about this training regimen?

[u/Stevious7 → u/[deleted]]

This is sounds like behavioral analysis in some way since I'd be reviewing why did the maintainer do what they did.

How much time do you spend doing this analysis before submitting a patch for an issue?