Temporal Convolutional Networks for Just-in-Time Software Defect Prediction

Pasquale Ardimento, Lerina Aversano, Mario Bernardi, Marta Cimitile

2020

Abstract

Defect prediction and estimation techniques play a significant role in software maintenance and evolution. Recently, several research studies proposed just-in-time techniques to predict defective changes. Such prediction models make the developers check and fix the defects just at the time they are introduced (commit level). Nevertheless, early prediction of defects is still a challenging task that needs to be addressed and can be improved by getting higher performances. To address this issue this paper proposes an approach exploiting a large set of features corresponding to source code metrics detected from commits history of software projects. In particular, the approach uses deep temporal convolutional networks to make the fault prediction. The evaluation is performed on a large data-set, concerning four well-known open-source projects and shows that, under certain considerations, the proposed approach has effective defect proneness prediction ability.

Paper Citation

in Harvard Style

Ardimento P., Aversano L., Bernardi M. and Cimitile M. (2020). Temporal Convolutional Networks for Just-in-Time Software Defect Prediction.In Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-443-5, pages 384-393. DOI: 10.5220/0009890003840393

in Bibtex Style

@conference{icsoft20,
author={Pasquale Ardimento and Lerina Aversano and Mario Bernardi and Marta Cimitile},
title={Temporal Convolutional Networks for Just-in-Time Software Defect Prediction},
booktitle={Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2020},
pages={384-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009890003840393},
isbn={978-989-758-443-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Temporal Convolutional Networks for Just-in-Time Software Defect Prediction
SN - 978-989-758-443-5
AU - Ardimento P.
AU - Aversano L.
AU - Bernardi M.
AU - Cimitile M.
PY - 2020
SP - 384
EP - 393
DO - 10.5220/0009890003840393