You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Spectrum Impact Analysis of Fault Proneness Statement for Improved Fault Localization

Authors:

Md Alamgir Kabir , M M Manjurul Islam , S.M. Hasan Mahmud , Md Fazla Elahe

Publication Type:

Conference/Workshop Paper


Abstract

Background: Fault localization is an important approach aimed at discovering faults in source codes to accelerate the activities of software development and maintenance. Spectrum-based fault localization (SBFL) techniques have been widely used to find faults. Ranking the fault-proneness statement is a promising research topic and several methods have been proposed in research in recent decades. Aim: To facilitate and interpret ranked files by software quality teams, we thoroughly explore and examine the effectiveness and importance of SBFL in locating faults by utilizing statement-hit spectra. Method: We conduct an empirical study for classifying fault-prone statements by adopting ranking-based fault localization approaches. We set up an experimental environment named Classification of Fault Proneness Statement (CFPS) that automatically classifies fault-prone statements (from very high to low). We conduct an extensive set of experiments on real-world dataset, which are coded and complied in C programming language, to validate the proposed methodology. The experiments are compared and evaluated with four state-of-the-arts similarity coefficient ranking algorithms. Results: Our experiment reveals that the similarity coefficient, tarantula significantly outperforms the others when validated with CFPS. Tarantula with CFPS achieves the score of Mean Average Precision (MAP) and Mean Reciprocal Rank (MRR) 33.27% and 32.91%, respectively on average across the selected experimented programs. Conclusions: The empirical study demonstrates the positive impact and effectiveness of SBFL and CFPS in classifying fault-prone statements. Furthermore, CFPS provides extra and essential information to developers for accurate fault localization and should be considered by software quality teams. The data and codes are released at https://github.com/sagarwhu/SBFL.

Bibtex

@inproceedings{Kabir 6537,
author = {Md Alamgir Kabir and M M Manjurul Islam and S.M. Hasan Mahmud and Md Fazla Elahe},
title = {Spectrum Impact Analysis of Fault Proneness Statement for Improved Fault Localization},
month = {August},
year = {2022},
url = {http://www.es.mdu.se/publications/6537-}
}