Earticle

초록

영어

Spectrum-based Fault Localization (SBFL) has been proven to be an effective technique to locate faulty statement in program code. SBFL metrics exploit the records of statement execution (spectra) by pass and fail test cases for each statement to rank its likeliness to be faulty. However, in some cases, these spectra contain duplicated and ambiguous information or noise which may deteriorate the performance of SBFL metrics. We propose six noise reduction schemes to eliminate test cases which provide duplicated and ambiguous information and evaluate the resulting performance improvements in SBFL metrics. Based on our findings, we further provide a guide for SBFL practitioners to select the best performing noise reduction scheme for the SBFL metrics that they use.

목차

Abstract
 1. Introduction
 2. Preliminaries
  2.1. Software Artifacts Used for Empirical Study
  2.2. Spectrum-based Fault Localization Metrics
 3. Problem
 4. Proposed Noise Reduction Schemes
 5. Experiment Results
 6. Discussion
 7. Conclusion
 Acknowledgements
 References

키워드

저자

• Patrick Daniel [ Faculty of Engineering, Computing and Science Swinburne University of Technology, Kuching, Sarawak, Malaysia ]
• Kwan Yong Sim [ Faculty of Engineering, Computing and Science Swinburne University of Technology, Kuching, Sarawak, Malaysia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605