Software Engineering Lab of Beijing Institute of Technology (BIT) BITSE-Lab
The Software Engineering Lab of Beijing Institute of Technology (BITSE-Lab) maintains an open-source organization on GitHub, aiming to systematically present the lab’s research and engineering outcomes in the field of Software Engineering and Open Source Software (OSS), while providing a unified, open, and reproducible collaboration platform for research and teaching activities.
🔗 GitHub Organization: 👉 https://github.com/bitse-lab
This organization serves as a centralized hub for:
- 📦 Research code and experimental artifacts
- 🧪 Prototypes and proof-of-concept systems
- 🛠️ Research tools and engineering implementations
By leveraging open-source practices, BITSE-Lab actively promotes:
- ✅ Research reproducibility
- 🔁 Experimental replication and data sharing
- 🤝 Community collaboration and knowledge dissemination
https://github.com/bitse-lab/awesome-git-commit
Evaluating Generated Commit Messages with Large Language Models
This project investigates the problem of automated evaluation of generated commit messages. Traditional reference-based metrics such as BLEU, ROUGE-L, and METEOR exhibit significant limitations in this task due to the non one-to-one mapping between code changes and commit messages.
We systematically explore:
- Large Language Models (LLMs) as automatic evaluators
- Prompting strategies including Few-shot learning and Chain-of-Thought reasoning
- Evaluation robustness, fairness, and reproducibility
Our results show that LLM-based evaluators can achieve near-human-level evaluation quality, significantly outperforming conventional automatic metrics.
https://github.com/bitse-lab/conventional-commit-classification
A First Look at Conventional Commits Classification
This repository presents an empirical study on the Conventional Commits Specification (CCS) and its adoption in open-source projects.
Key contributions include:
- An empirical analysis of CCS usage in real-world repositories
- Identification of common misclassification patterns
- A refined and less overlapping definition set for commit types
- An automated approach for conventional commit classification
📦 The repository contains all datasets, models, and experimental code used in the study.
https://github.com/bitse-lab/python-supply-chain
Python Software Supply Chain Construction and Visualization Tool
This project is an open-source tool designed for Python developers, security researchers, and system administrators, focusing on:
- Python dependency resolution
- Software supply chain construction
- Vulnerability discovery and analysis
Key features:
- Accurate supply chain construction without installing packages
- Optimized pip dependency resolution algorithm
- Integrated CVE vulnerability lookup
- Interactive visualization through a front-end interface
🧱 Architecture:
- Front-end: Vue.js + Element UI
- Back-end: Django-based REST APIs
This tool supports both academic research and practical security analysis in the Python ecosystem.
https://github.com/bitse-lab/OSSMirror
This repository supports research on open-source ecosystem analysis, mirroring, and large-scale data collection, providing infrastructure for reproducible OSS experiments.
The BITSE-Lab GitHub organization also supports:
- 📘 Open source software engineering courses
- 🧑🎓 Undergraduate and graduate research training
- 🧪 Experimental replication and benchmarking
- 🤝 Academic and industrial collaboration
Students and researchers are welcome to explore, reproduce, and build upon our work.
We welcome contributions in the form of:
- Issues and pull requests
- Experimental reproduction and feedback
- Research collaboration
- Teaching and educational use
Please feel free to contact us through GitHub.
Each repository follows its own declared open-source license unless otherwise specified.