Mining Developer Expertise from Bug Tracking Systems using the Author-topic Model

Daniel Atzberger, Jonathan Schneider, Willy Scheibel, Daniel Limberger, Matthias Trapp, Jürgen Döllner

2022

Abstract

During the software development process, software defects, so-called bugs, are captured in a semi-structured manner in a bug tracking system using textual components and categorical features. It is the task of the triage owner to assign open bugs to developers with the required skills and expertise. This task, known as bug triaging, requires in-depth knowledge about a developer’s skills. Various machine learning techniques have been proposed to automate this task, most of these approaches apply topic models, especially Latent Dirichlet Allocation, for mining the textual components of bug reports. However, none of the proposed approaches explicitly models a developer’s expertise. In most cases, these algorithms are treated as a black box, as they allow no explanation about their recommendation. In this work, we show how the Author-Topic Model, a variant of Latent Dirichlet Allocation, can be used to capture a developer’s expertise in the latent topics of a corpus of bug reports from the model itself. Furthermore, we present three novel bug triaging techniques based on the Author-Topic Model. We compare our approach against a baseline model, that is based on Latent Dirichlet Allocation, on a dataset of 18 269 bug reports from the Mozilla Firefox project collected between July 1999 to June 2016. The results show that the Author-Topic Model can outperform the baseline approach in terms of the Mean Reciprocal Rank.

Paper Citation

in Harvard Style

Atzberger D., Schneider J., Scheibel W., Limberger D., Trapp M. and Döllner J. (2022). Mining Developer Expertise from Bug Tracking Systems using the Author-topic Model. In Proceedings of the 17th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-568-5, pages 107-118. DOI: 10.5220/0011045100003176

in Bibtex Style

@conference{enase22,
author={Daniel Atzberger and Jonathan Schneider and Willy Scheibel and Daniel Limberger and Matthias Trapp and Jürgen Döllner},
title={Mining Developer Expertise from Bug Tracking Systems using the Author-topic Model},
booktitle={Proceedings of the 17th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2022},
pages={107-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011045100003176},
isbn={978-989-758-568-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Mining Developer Expertise from Bug Tracking Systems using the Author-topic Model
SN - 978-989-758-568-5
AU - Atzberger D.
AU - Schneider J.
AU - Scheibel W.
AU - Limberger D.
AU - Trapp M.
AU - Döllner J.
PY - 2022
SP - 107
EP - 118
DO - 10.5220/0011045100003176