README.md

---
license: mit
datasets:
- bug-localization/BeetleBox
- princeton-nlp/SWE-bench
language:
- en
base_model:
- codesage/codesage-base
tags:
- bug
- localization
- embedding
- multi-language
---

# 🔥 BLAZE: Cross-Language and Cross-Project Bug Localization

**BLAZE** is a transformer-based bug localization model that works across languages and software projects. It enhances source-bug alignment using **dynamic chunking** and **hard example learning**, enabling precise bug localization in unseen codebases and programming languages.

[![Paper](https://img.shields.io/badge/Paper-TSE%202025-blue)](https://doi.org/10.1109/TSE.2025.3579574)
[![Dataset](https://img.shields.io/badge/Dataset-Zenodo-9cf)](https://zenodo.org/records/15122980)

---

## ✨ Highlights

* 📌 **Cross-project & cross-language** bug localization with no re-training
* 📏 **Dynamic Chunking** handles long files within LLM context windows
* 🧠 **Hard Example Learning** improves generalization and ranking accuracy
* 🌍 Supports Java, Python, C++, JavaScript, and Go
* 📊 Outperforms both cross-project and embedding-based baselines

---

## 📂 Dataset: BeetleBox

**BeetleBox** is the largest curated dataset for bug localization:

* 23,782 real-world bugs
* 29 repositories
* 5 programming languages
* Cleaned and de-duplicated to remove overlaps with training data

📥 [Available on Zenodo](https://zenodo.org/records/15122980)
📚 Also listed on Hugging Face Datasets: `bug-localization/BeetleBox`

---

## 🚀 Demo & Usage

All code, usage instructions, model files, and scripts are available via:

👉 **[BLAZE Repository & Demo (Zenodo)](https://zenodo.org/records/15122980)**

---

## 📝 Citation

Please cite the following paper if you use BLAZE or BeetleBox in your work:

```bibtex
@article{Chakraborty2025,
  title = {BLAZE: Cross-Language and Cross-Project Bug Localization via Dynamic Chunking and Hard Example Learning},
  ISSN = {2326-3881},
  url = {http://dx.doi.org/10.1109/TSE.2025.3579574},
  DOI = {10.1109/TSE.2025.3579574},
  journal = {IEEE Transactions on Software Engineering},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  author = {Chakraborty, Partha and Alfadel, Mahmoud and Nagappan, Meiyappan},
  year = {2025},
  pages = {1--14}
}
```