Summary
In this chapter, we’ve discussed LLMs for source code and how they can help in developing software. There are quite a few areas where LLMs can benefit software development, mostly as coding assistants. We’ve applied a few models for code generation using naïve approaches and we’ve evaluated them qualitatively. In programming, as we’ve seen, compiler errors and results of code execution can be used to provide feedback. Alternatively, we could have used human feedback or implemented tests.
We’ve seen how the suggested solutions seem superficially correct but don’t perform the task or are full of bugs. However, we can get a sense that – with the right architectural setup – LLMs could feasibly learn to automate coding pipelines. This could have significant implications regarding safety and reliability. As for now, human guidance on high-level design and rigorous review seem indispensable to prevent subtle errors...
