Writing that changed how I think about PL

Every so often I come across a paper, blog post, or (occasionally) video that completely changes how I think about a topic in programming languages and compilers. For some of these posts, I can’t even remember how I thought about the idea before reading it—it was that impactful.

Here are some of those posts in no particular order:

• a simple semi-space collector by Andy Wingo brought the concept of a Cheney/copying/compacting garbage collector from theory to practice for me. The garbage collector core¹ in the post is tiny, extensible, and can be understood in an afternoon.
• Implementing a Toy Optimizer by CF Bolz-Tereick changed how I think about instruction rewrites in an optimizer. No more find-and-replace. Instead, use a forwarding pointer! I love union-find. The whole toy optimizer series is fantastic: each post brings something new and interesting to the table.
• A Knownbits Abstract Domain for the Toy Optimizer, Correctly by CF Bolz-Tereick is a two-for-one. It both introduced me to a new abstract domain for optimizers and changed how I think about Z3. Before, I vaguely knew about Z3 as this thing that can check numeric operations, kind of. The post, however, uses Z3 as a proof engine: if Z3 can’t find a counterexample, the code is correct². Furthermore, it uses Z3 as a verifier for Python code by using the same Python code on both Z3 objects and normal Python objects.
• Cranelift, Part 3: Correctness in Register Allocation by Chris Fallin also made proofs more accessible, but in a different way. Instead of proving your register allocator correct on all inputs, prove it correct on one input: the current code. This means that in production, you either get a correct register allocation or a meaningful crash. Additionally, it uses fuzzing as a state space exploration tool that can identify bugs by making the verifier fail.
• Regular Expression Matching: the Virtual Machine Approach by Russ Cox made regular expression engines make sense to me. In the blog post is a small regular expression engine in under 50 lines of readable code. As a side effect, it also made coroutines/fibers/schedulers more understandable because its implementation of nondeterminism makes regex “threads” in user-space.
• micrograd by Andrej Karpathy is a tiny implementation of neural networks with no libraries (not even NumPy). It’s how I came to understand machine learning and even write some blog posts about it.
• How I implement SSA form by Fil Pizlo changed how I think about union-find. Instead of either storing an additional pointer inside every object or having a side-table, add an Identity tag that can store the pointer. Unlike the other two approaches, this is a destructive rewrite, but it saves space. It also introduces two new things that I am still mulling over: Phi/Upsilon form and TBAA-style heap effects.
• Speculation in JavaScriptCore is another absolute banger by Fil Pizlo. I learn new things every time I re-read this post, which describes how JSC’s various optimizers work (and I guess how Fil thinks about optimizers).
• Modernizing Compiler Design for Carbon Toolchain is a talk by Chandler Carruth on the design of the Carbon compiler. About 29 minutes into it Chandler sets incredibly aggressive compile-time budgets and explains how the compiler is architected to fit in that time budget. At around 40 minutes, he starts explaining per-layer how this works, starting at the lexer.
• A Python Interpreter Written in Python by Allison Kaptur made bytecode interpreters (and, specifically, how CPython works internally) click for me.
• Parsing expressions by precedence climbing by Eli Bendersky presented an understandable and easier-to-develop alternative to traditional hand-written recursive descent parsers. It both made parsers less scary to me and also at the same time illustrated how precedence climbing is the same algorithm as recursive descent but instead of having 10 different functions with similar structure, it uses one function and a table.
• Ruby JIT Challenge by Takashi Kokubun is a great start to code generation and it is more general than JIT, too. In the post he also shows off a cool approach to register allocation that I had not seen before: fold your stack operations at compile-time to operate on a virtual stack of physical registers.
• An Incremental Approach to Compiler Construction (PDF) by Abdulaziz Ghuloum brought compilers and code generation from a mystical multi-pass beast down to an understandable single-pass form. I like how it implements each feature end-to-end, one by one.
• Lessons from Writing a Compiler by Fernando Borretti puts into words this stripey implementation strategy in the first section, which is really neat.
• egg: Fast and extensible equality saturation by [multiple authors] changed how I think about optimizers and pass ordering. Why not just generate the compressed hypergraph of all possible versions of an expression and then pick the “best” one? I mean, there are a couple of reasons, but it was mind-expanding.
• Cranelift: Using E-Graphs for Verified, Cooperating Middle-End Optimizations by Chris Fallin showed that e-graphs are workable and remarkably effective in a production compiler, even if you don’t do the “full shebang”.
• Acyclic Egraphs and Smart Constructors by Phil Zucker further explores acyclic egraphs in the small. This one was a slow burn: I read it when it came out, didn’t really get it, and then months later it clicked more. I’m sure that in a few months it’ll click again.
• This Reddit comment by Bob Nystrom and Flattening ASTs by Adrian Sampson are a double whammy that led to two things: 1) AST storage can be really compact, almost like bytecode 2) a really interesting discussion on Mastodon about massively-parallel lock-free abstract interpretation if IRs were stored like this. This (and some off-hand comments by Cliff Click about bump-allocation only taking “a few clocks”) changed how I think about allocating and referring to IR nodes.

I hope you enjoy the readings!