Learning a code-base in a new language - How to do it?

C++ is a rough language to learn - I know this because C++ was the primary language for UCLA Computer Science back in my day. It's pretty verbose and a lot of stuff doesn't come "for free" (like automatic garbage collection). It can be hard picking up C++ if you're used to a more streamlined language like Python or even Java.

Should I spend time learning the language before diving into the code or otherwise?

It's probably worth it going through a course or book that covers the absolute basics of C++. I looked at W3 Schools' C++ material briefly and it seems decent: https://www.w3schools.com/cpp/

If books are your thing, they can be effective for "101-style" material (classes, variables, etc), because it's all evergreen. I forget which book we used at UCLA, but this one seems solid: C++ All-in-One For Dummies

On top of these, I still recommend the usual advice of playing around with the code, seeking lots of help from teammates, and all that good stuff. These resources cover that in more detail:

• "What is the effective way to understand new repository in order to make the required changes in that repo?"
• "How can I pick up other tech stacks more quickly at Meta?"
• "How do I identify the core things to learn when picking up a new tech stack?"

Something else I'll mention is that there's nothing wrong with shamelessly copy-pasting 😉. At a Big Tech company like TikTok, it's not likely that you'll get a coding task (especially if you're onboarding) where the code is completely novel and unlike something else that already exists in the codebase.

At Meta, my strategy working in an unfamiliar codebase was often:

1. Find a commit that does something similar to what I'm doing
2. Copy-paste the code
3. Desperately guess and change the variables and other parameters to make the code adhere to my use-case
4. Run the code and hope it meets success criteria
5. Repeat #3 and #4 until it works. If I get stuck, ask for help

From Step #4, verifying that stuff works often won't be fully defined on your task (e.g. "How do I run my new API endpoint, send it data, and verify the response?"). If that's the case, aggressively push to clarify this. This is the most important piece of going through the feedback loop of trying stuff and seeing if it works.

This type of basic pattern matching is also something AI can be really good at. Maybe you can get permission from your manager to integrate GitHub Copilot or feed large amounts of your team's C++ code into ChatGPT? Here's the case study we recently gave about the topic: [Case Study] How Engineers Unlock Huge Impact With Artificial Intelligence (AI)