A novel approach for mutant diversity-based fault localization: DAM-FL

ABSTRACT

Locating faults after detecting is one of the important steps in software debugging. For fault localization, many approaches are there. Mutant based approaches are also available for fault localization and they have performed better compared to statement based approaches. In the present paper, a new mutant based fault localization approach named “DAM-FL” is proposed which is based on diversity aware mutation adequacy criterion. It uses diversified or distinguished mutants and their respective test suites for locating faults. Experiments on projects of defects4j repository show that for single line faults, proposed approach with a reduced number of mutants performs better or gives similar results compared to the traditional mutant based fault localization approach. For multi-line faults, it can be said that the proposed approach is equivalent to the traditional approaches.

KEYWORDS:

• Fault localization
• mutant-based fault localization approaches
• fault detection
• diversified mutants

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Number after project name represents the number of bugs in that project.

 

Additional information

Notes on contributors

Neha Gupta

Neha Gupta received her B.Tech degree in Computer Science & Engineering from Maharshi Dayanand University, India, in 2011, and M.Tech degree in Software Engineering from Delhi Technological University, India, in 2014. She is currently pursuing Ph.D. degree with the Department of Information Technology, Indira Gandhi Delhi Technical University for Women, India. Her research interests include optimization techniques, software testing, and cost estimation.

Arun Sharma

Arun Sharma received the Ph.D. degree from Thapar University, Patiala, in 2009. He is currently an Associate Professor of IT with the Indira Gandhi Delhi Technical University for Women, Delhi. Under his guidance, six students have completed their Ph.D. degree. He has published more than 60 papers in SCI/SCIE/SCOPUS and other international journals and conferences including IEEE, ACM, Springer, Elsevier, Wiley, and several others. His areas of interests include software engineering, autonomic systems, soft computing, and big data.

Manoj Kumar Pachariya

Manoj Kumar Pachariya received the master's degree from UP Technical University and the Ph.D. degree from Thapar University, Patiala, India. He is currently an Associate Professor with the Department of Computer Science and Applications, Makhanlal Chaturvedi National University of Journalism and Communication, Bhopal, India. He has published several research papers in international journals indexed in SCI and Scopus journals. His research interest includes software engineering focusing on software testing, software quality, multi-objective optimization, component-based software development, soft computing, evolutionary computing, and nature inspired computing techniques. He is a member of several professional bodies including CSI, IEEE, ACM, SCRS, and International Association of Engineers Society. He is an Editorial Board Member of various international journals.