A pluginable code comprehension tool for large-scale C/C++, C#, and Python software with deep parsing and visualization.
CodeCompass is a pluginable code comprehension tool that helps developers understand and navigate large-scale software written in C/C++, C#, and Python. It provides deep parsing, visualization diagrams, and a web-based interface to explore code structure and dependencies. The tool is designed to improve code maintainability and reduce complexity in large projects.
Software developers, architects, and maintainers working with large C/C++, C#, or Python codebases who need to analyze, refactor, or understand complex software systems.
Developers choose CodeCompass for its deep language parsing, scalable performance on large codebases, and rich visualization features like call path and inheritance diagrams, all accessible through an intuitive web UI.
CodeCompass is a software comprehension tool for large scale software written in C/C++, C# and Python.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
The user-friendly web UI allows code exploration from any browser, eliminating the need for local tool installation, as highlighted in the features section.
Supports deep parsing for C, C++, and Java, with additional support for C# and Python, enabling comprehensive analysis of mixed-language codebases, as stated in the README.
Provides various diagrams like call path, inheritance, and CodeBites to visually represent code relationships, aiding in understanding complex structures, as shown in the screenshots.
Designed for quick response times even with large source code bases up to 100MB, making it suitable for enterprise-scale software, per the features list.
The README includes links to building and dependency guides, indicating that installation and configuration require significant effort, especially for custom deployments.
Deep parsing is primarily for C, C++, and Java, with C# and Python having less comprehensive analysis, and support for other languages is minimal or pending, as noted in the features.
Relies entirely on a web interface, which may not be suitable for offline environments or teams preferring native or command-line tools without browser overhead.