🧩 WASM Modules

Module Linking, Component Model, Interface Types, Runtime Composition

Cactus Language • Syntax 12
inquiryintoinquiry.com·10h
📝Concrete Syntax
Building a unified homelab documentation & infrastructure management platform - looking for feedback from the community
reddit.com·1d·
Discuss: r/homelab
🏠Homelab Preservation
BNFGen: A random text generator based on context-free grammars
baturin.org·8h·
Discuss: Hacker News
🌳Context free grammars
Reducing tool calling error rates for OpenAI, Anthropic, and Gemini models
mastra.ai·3d·
Discuss: Hacker News
✅Format Verification
Driving the Rust Compiler to Compile Single Files as Shellcode
kirchware.com·2d·
Discuss: Hacker News
🦀Rust Macros
Just some example work notes
dev.to·3d·
Discuss: DEV
💧Liquid Types
Deep Dive into Databend UDF, implementing your data solutions with python, WASM and beyond
dev.to·7h·
Discuss: DEV
📋DFDL
NaviAgent: Bilevel Planning on Tool Dependency Graphs for Function Calling
arxiv.org·22h
🔗Topological Sorting
How to Prompt an LLM to Write Angular Code: Straight from the Experts
dev.to·1d·
Discuss: DEV
🔗Concatenative Programming
Flame Graph Performance Truth Analysis（1750839255230100）
dev.to·18h·
Discuss: DEV
⚡Performance Tools
Logic App Http Connector with Swagger + C# Function App
dev.to·3d·
Discuss: DEV
🔐CBOR
Explaining software and computational methods
blog.khinsen.net·1d·
Discuss: Hacker News
📝Concrete Syntax
LLMs bring new nature of abstraction
martinfowler.com·1d·
Discuss: Hacker News
💻Programming languages
Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training
arxiv.org·1d
💻Local LLMs
Software Architecture Styles : Monolith, Modulith, Micro-services, which option is better for you
dev.to·5h·
Discuss: DEV
⚡SMT Applications
Machine Learning Fundamentals: active learning project
dev.to·11h·
Discuss: DEV
🧠Machine Learning
Heartbeat of Modern Web Real Time Patterns User Design（1750804864723400）
dev.to·1d·
Discuss: DEV
🌊Stream Processing
Build, Celebrate, collaborate: Microsoft SharePoint Web Parts That Do It All
dev.to·16h·
Discuss: DEV
🧠Personal Knowledge Base
Exploring High Efficiency Web Analysis Results（1750876031390300）
dev.to·8h·
Discuss: DEV
🌊Stream Processing
An Expert Survey on Models and Digital Twins
arxiv.org·1d
⚙️TLA+