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#haskell

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I'm writing a series of blog posts, in which I write a #bytecode #compiler and a #virtualMachine for arithmetic in #Haskell. We explore the following topics in the series:

- Parsing arithmetic expressions to ASTs.
- Compiling ASTs to bytecode.
- Interpreting ASTs.
- Efficiently executing bytecode in a VM.
- Disassembling bytecode and decompiling opcodes for debugging and testing.
- Unit testing and property-based testing for our compiler and VM.
- Benchmarking our code to see how the different passes perform.
- All the while keeping an eye on performance.

The second post of the series that focuses on writing the #compiler is now out: abhinavsarkar.net/posts/arithm

abhinavsarkar.net · A Fast Bytecode VM for Arithmetic: The Compiler
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Antwortete im Thread

@matt There is something really elegant about #Haskell, and its isolation of "pure" functions (which can't perform I/O) from impure functions, as well as general data immutability, make for nice designs that are easy to reason about, and excellent recursion handling also feeds into that.

That said, memory usage in Haskell can be hard to reason about, and Rust gives some of those guarantees with its "mut" keyword.

I do a lot of systems programming, so would mostly go for Rust these days.