Metadata-Version: 2.1
Name: fse-baro
Version: 0.0.8
Summary: BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection
Author-email: Luan Pham <phamquiluan@gmail.com>
License: MIT License
        
        Copyright (c) 2024 Luan Pham
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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        The above copyright notice and this permission notice shall be included in all
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Project-URL: Homepage, https://github.com/phamquiluan/baro/
Project-URL: Issues, https://github.com/phamquiluan/baro/issues
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: pytest
Requires-Dist: tqdm
Requires-Dist: requests
Requires-Dist: matplotlib

# BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection

[![pypi package](https://img.shields.io/pypi/v/fse-baro.svg)](https://pypi.org/project/fse-baro)
[![Build and test](https://github.com/phamquiluan/baro/actions/workflows/build-and-test.yml/badge.svg?branch=main)](https://github.com/phamquiluan/baro/actions/workflows/build-and-test.yml)

BARO is an end-to-end approach to perform anomaly detection and root cause analysis for microservices's failures. This repository contains the artifact for reproducing the main experimental results in our paper accepted to ESEC/FSE 2024, and reusing purposes.


## Installation

Install from [PyPI](https://pypi.org/project/fse-baro)

```bash
pip install fse-baro
```

Or, build from source

```bash
git clone https://github.com/phamquiluan/baro.git && cd baro
pip install -e .
```

More details are in [INSTALLATION.md](INSTALLATION.md).

## How-to-use

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1znckFNPny9zU0Rlc9_Q99E6h3hsJq764?usp=sharing)


```python
from baro import BARO

m = BARO()

anomalies = m.detect_anomalies(data)
root_causes = m.rca(data, anomalies=anomalies)
print(root_causes)
```

## Download Paper

TBD

## Download Datasets

Our datasets are publicly available in Zenodo repository with the following information:

- Dataset DOI: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11046533.svg)](https://doi.org/10.5281/zenodo.11046533)
- Dataset URL: https://zenodo.org/records/11046533

## Reproducibility

Check the Jupyter Notebook at [tutorials/reproducibility.ipynb](https://github.com/phamquiluan/baro/blob/main/tutorials/reproducibility.ipynb) to reproduce the performance of BARO.

## Citation

```
@inproceedings{pham2024baro,
  title={BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection},
  author={Luan Pham, Huong Ha, and Hongyu Zhang},
  booktitle={Proceedings of the ACM on Software Engineering, Vol 1},
  year={2024},
  organization={ACM}
}
```

## Contact

[luan.pham\@rmit.edu.au](mailto:luan.pham@rmit.edu.au?subject=BARO)
