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Authors: Chun Yong Chong 1 and Sai Peck Lee 2

Affiliations: 1 School of Information Technology, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor and Malaysia ; 2 Department of Software Engineering, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603 and Malaysia

ISBN: 978-989-758-320-9

Keyword(s): Software Fault Identification, Software Change Coupling, Commit Change Data, Mining Software Repositories, Complex Network.

Abstract: Over the past few years, attention has been focused on utilizing complex network analysis to gain a high-level abstraction view of software systems. While many studies have been proposed to use interactions between software components at the variable, method, class, package, or combination of multiple levels, limited studies investigated how software change history and evolution pattern can be used as a basis to model software-based weighted complex network. This paper attempts to fill in the gap by proposing an approach to model a commit change-based weighted complex network based on historical software change and evolution data captured from GitHub repositories with the aim to identify potential fault prone classes. Experiments were carried out using three open-source software to validate the proposed approach. Using the well-known change burst metric as a benchmark, the proposed method achieved average precision of 0.77 and recall of 0.8 on all the three test subjects.

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Paper citation in several formats:
Yong Chong, C. and Peck Lee, S. (2018). A Commit Change-based Weighted Complex Network Approach to Identify Potential Fault Prone Classes.In Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-320-9, pages 437-448. DOI: 10.5220/0006828104710482

@conference{icsoft18,
author={Chun Yong Chong. and Sai Peck Lee.},
title={A Commit Change-based Weighted Complex Network Approach to Identify Potential Fault Prone Classes},
booktitle={Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2018},
pages={437-448},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006828104710482},
isbn={978-989-758-320-9},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - A Commit Change-based Weighted Complex Network Approach to Identify Potential Fault Prone Classes
SN - 978-989-758-320-9
AU - Yong Chong, C.
AU - Peck Lee, S.
PY - 2018
SP - 437
EP - 448
DO - 10.5220/0006828104710482

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