EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Sep 11·5 min read
If coding is solved, what now?: Measuring the sloppiness of code
TL;DR
As large language models (LLMs) excel at generating code, the challenge now lies in addressing the 'sloppiness' of that code, which can lead to unnecessary complexity and duplication. A quantitative approach to measuring code quality is essential to regain human control over rapidly expanding codebases.
✦ Why It Matters
Start implementing code quality metrics to assess and improve your projects today.
Key Takeaways
- Measure code quality using metrics like verbosity and erosion.
- Be cautious of LLMs producing overly complex code.
- Incorporate human review to ensure code readability.
- Monitor code growth to prevent accumulation of bad decisions.
How It Works
The author developed metrics to quantify code sloppiness, focusing on 'verbosity' (duplication and unnecessary lines) and 'erosion' (complexity concentration in functions). These metrics provide a clearer picture of code quality compared to subjective evaluations.