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High-Performance Code Analysis Engine for Claude Code in C++17

#claudecode #javascript #cpp #python

Background and Motivation

The need for high-speed code analysis for AI development with tools like Claude Code.

The Python version reached its performance limits in large-scale projects.

Re-implemented in C++17 to achieve a 10-100x performance improvement.
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Technical Choices

Parser Selection

From std::regex to PEGTL (Parsing Expression Grammar Template Library)

Escaping "regex hell."
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Parallel Processing Design

Leveraging std::execution::par_unseq

Controlling I/O thread count (--io-threads)

Optimizing CPU-bound processing
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Implementation Innovations

Language-Specific Hybrid Strategy

TypeScript: PEGTL + string parsing fallback

C++: Support for template and macro parsing

Python: Special handling for indentation-based syntax
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Memory Optimization

180x speed improvement through session management

Caching strategy
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Results and Measured Performance

Project Number of Files Detected Functions Processing Time
TypeScript Compiler 735 files 2,362 functions 1.9 minutes
lodash.js 1 file 489 functions 0.7 seconds
nlohmann/json 1 file 254 functions 0.5 seconds

What We Learned

The limitations of regular expressions and alternative methods

The practicality of C++17 parallel processing

The importance of a language-specific parsing strategy
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Future Outlook

Support for more languages

Optimization specifically for Claude Code
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Source Code

GitHub: https://github.com/moe-charm/nekocode

Video Demo

See it in action here: https://www.youtube.com/watch?v=I9Nij1KgTPw

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