| > We didn't write this parser by hand because, at least pre-AI-coding, parsers were extremely difficult to maintain. Writing one without AI would have taken months [...] > Instead, we use ANTLR, a state-of-the-art, open source parser generator. I don't agree with this (pre-AI-coding) take. Hand-rolled parsers are much easier to write well and maintain than people think. They also tend to be much faster and produce much better errors than parser generators. I guess if the language you're trying to parse is, say, C++, then you're going to have a miserable time (probably no matter what). But an SQL parser is very doable. (I say this as the author and maintainer of an in-house SQL dialect thingy at work.) What makes building and maintaining a hand-written parser such a tractable task is: - The code size can be large, but you can start with a core of a few well-chosen abstractions and then you add lots of parsing code for various language constructs but it's all kind of orthogonal and doesn't add compounding complexity as you go.
- It's just about the most testable kind of code there is. You can cover all the various corner cases with tests and really lock in the behavior so that you can very confidently make changes. One approach I like is to make zillions of tiny test files in the target language accompanied by some golden representation of the AST. And of course, as the author found out, these properties make writing a parser a really good task for AI coding, too. These tools are very, very good at generating a bunch of new code based on existing abstractions and covering it with lots of test cases. So I agree with where they ended up, just not where they started :) |