code-complexity
There are 17 repositories under code-complexity topic.
Melevir/flake8-cognitive-complexity
An extension for flake8 that validates cognitive functions complexity
mosesliao/fastlane-plugin-lizard
🦎Official fastlane plugin for lizard code complexity analytics 🦎
iepathos/debtmap
Technical debt analyzer with coverage-aware risk scoring and actionable refactoring recommendations
coderstats/todomvc-metrics
Measure the complexity of TodoMVC implementations
Kranf99/IOKranf
Educational library in Javascript that is great for kids to learn programming. This library emulates a "console" with simple println and input command.
Ayushx309/codemetrix
🔍 CodeMetrix: A sophisticated code analysis and cost estimation tool that provides advanced metrics, quality assessment, and intelligent reporting for software projects. Features COCOMO II modeling, AST-based analysis, and multi-language support.
TomasVotruba/shopsys-spryker-and-sylius-analysis
Static analysis of Shopsys, Sylius and Spryker
amanv8060/code-complexity-viz
A simple tool to analyzing and visualizing code complexity metrics in go.
moe-charm/nekocode
⚠️ MOVED to nekocode-rust - 16x faster, 96% smaller. See github.com/moe-charm/nekocode-rust
KamruzzamanAsif/SPL-1
Static Code Analyzer (SCA) analyzes the ‘C’ source codes without executing the program. It determines the software metrics (such as LOC and Halstead Complexity metrics) and detect syntactic code clones.
mmohajer9/pyccmetrics
Python package for calculating code complexity metrics of the target source code.
pasanjg/CODEX
Code Complexity measuring tool developed in REST
svemyh/Real-Time-Elevator
Real Time Elevator Project - Software for controlling n elevators working in parallel across m floors
Blasanka/code-measuring-tool
This is the CDE IT Solutions code complexity measurement tool developed to measure Java and C++ programs by uploading file(s) and as zip.
bronek89/code-complexity
Class for check code complexity score of php code.
dessertlab/Human_vs_AI_Code_Quality
This repository allows the replication of our study "Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity" accepted for publication at The 36th IEEE International Symposium on Software Reliability Engineering (ISSRE 2025).