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About

About This Project

Based on a systematic review of 188 papers and online resources, this project establishes a holistic theoretical framework for Issue Resolution in software engineering. This website is designed to facilitate efficient literature retrieval and exploration.

Key Features

  • Comprehensive Coverage: Covers three major sections - Data, Methods, and Analysis
  • Convenient Retrieval: Supports full-text search and categorical browsing
  • Database-Driven: All paper and table data is managed in a local SQLite database
  • Admin Interface: Web-based admin panel at /admin for CRUD operations, arXiv auto-fill, and one-click site build
  • Two-Way Sync: Data can be exported to YAML/CSV (data/) or re-imported from files at any time

Common Operations

Goal Command / Action
Full update + start server python start.py (refreshes news, renders README/docs, builds site)
Re-import data then full update python start.py --init
Start server without updates python start.py --no-update
Refresh news section only python start.py --news
Re-render README/docs from DB python start.py --render or Render from DB in admin
Build static site only python start.py --build or Build Website in admin
Export DB → YAML/CSV Sync to Data in admin
Import YAML/CSV → DB Import from Data in admin

Contribution Guide

We welcome Pull Requests to add new papers or fix errors!

  1. Fork this repository
  2. Add paper entries in the corresponding YAML file under data/ directory (e.g., papers_evaluation_datasets.yaml, papers_single_agent.yaml, etc.)
  3. Follow the existing format with fields: short_name, title, authors, venue, month, and links (arxiv, github, huggingface)
  4. Run python start.py --render to regenerate the README and docs from the database
  5. Submit a PR with your changes

Acknowledgements

We would like to express our sincere gratitude to:

  • The authors of cited papers who provided valuable feedback on how their work is presented in this survey, greatly improving its accuracy and comprehensiveness.

  • All contributors who have helped improve this project through issues, pull requests, and discussions.

  • The open-source community for developing the amazing tools and frameworks that made this project possible.

Special Thanks

  • @chao-peng (Dr. Chao Peng), ByteDance Software Engineering Lab, for providing valuable suggestions on the Challenges and Opportunities section of our survey.

  • @EuniAI/awesome-code-agents for providing an excellent reference on managing survey papers through documentation systems and inspiring our project structure.

Interactive Exploration

NotebookLM Discord Issues

Contact Us

If you have any questions or suggestions, please contact us through GitHub Issues or email at [email protected].