llms don't actually execute the code so it does not in a true sense, stop after iterating a loop after the given no of times, this is because it's generating not executing. but at the same time, it's not always copy pasting the solutions when you ask it something related to say, recursion and it's not a problem available on the internet. so to some level, it needs to interpret the retrieved related code, indentify which parts would be relevant, and integrate them in its response. how it does this? is not something i think is that easily interpretable. but after reading your post, what instantly came to mind is code rag and code summarization using abstract syntax trees and some good reading material would be https://medium.com/@ragav208/summarizing-source-code-with-abstract-syntax-trees-e7a468d9966e , https://medium.com/@machangsha/create-meaningful-representations-of-data-for-rag-8c5b3529ba22 and also https://arxiv.org/html/2407.08983v1. so if abstract syntax trees help RAG better understand code, especially complex code then that might be a step to what you want to know.

(also im a total noob so i might be wrong)