How to Slow Down a Program? And Why it Can Be Useful.
stefan-marr.de·5h·
Discuss: Lobsters, Hacker News
🚀Compiler Optimizations
Abhinav Sarkar: A Fast Bytecode VM for Arithmetic: The Compiler
abhinavsarkar.net·3d
🔗Functional Compilers
Make and SQL: An old new way for Data Science workloads
vasvir.wordpress.com·21h·
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🦀Rust Macros
The Emacs thread-related code needs a maintainer
lists.gnu.org·6h·
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🦀Rust Macros
Anonymous structavaganza in zig
lirk.top·1d·
Discuss: Hacker News, r/Zig, r/programming
🔧Binary Parsers
Using panic metadata to recover source code information from Rust binaries | cxiao.net
cxiao.net·1d
🦀Rust Macros
Many hate on Object-Oriented Programming. But some junior programmers seem to mostly echo what they've heard experienced programmers say. In this blog post I tr...
zylinski.se·16h·
Discuss: Hacker News, r/programming
🔩Systems Programming
Wubular: Rubular Reimagined in Ruby+WASM
rubyelders.com·1d·
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🌀Brotli Internals
Log Detective: GSoC 2025 (part 2)
danigm.net·10h
🔓Open Source Software
Optimize Go Performance: Value vs. Pointer Types for Fewer Memory Allocations
dev.to·15h·
Discuss: DEV
🧠Memory Allocators
LLMs for Software Developers (notes from my talk at NWRUG)
theartandscienceofruby.com·4h·
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⚔️Lean Tactics
Nullable vs. Nullable in C#
einarwh.no·1d·
Discuss: Lobsters, Hacker News, r/programming
✅Format Verification
shared_ptr<T>: the (not always) atomic reference counted smart pointer (2019)
snf.github.io·14h·
Discuss: Lobsters, Hacker News, Hacker News
🦀Rust Borrowing
Chatting with Unmesh about building language with LLMs
martinfowler.com·1d
💻Programming languages
Typeclassopedia
wiki.haskell.org·2d·
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🧬Functional Programming
Chez Scheme vs. SBCL: a comparison (2019)
elmord.org·17h·
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🧠Lisp Dialects
Visual AI flow manager for Genkit – Looking for early testers
flowshapr.ai·1d·
Discuss: Hacker News
⚡Proof Automation
k-NN Classification and Model Evaluation
dev.to·1d·
Discuss: DEV
🧠Machine Learning
C++ or Rust: Differences Explained
harshal.is-cool.dev·5h·
Discuss: Hacker News
🔩Systems Programming
ConfTuner: Training Large Language Models to Express Their Confidence Verbally
arxiv.org·11h
🧠Intelligence Compression