An Approach of Improving the Efficiency of Software Fault Localization based on Feedback Ranking Information
-
Published:2023-09-15
Issue:18
Volume:13
Page:10351
-
ISSN:2076-3417
-
Container-title:Applied Sciences
-
language:en
-
Short-container-title:Applied Sciences
Author:
Yang Bo123, Ma Xiaowen1, Guo Haoran3, He Yuze3, Xu Fu12
Affiliation:
1. School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China 2. Engineering Research Center for Forestry Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China 3. School of Information Science and Technology, North China University of Technology, Beijing 100144, China
Abstract
Fault localization, a critical process of software debugging, can be implemented by ranking program statements according to their suspiciousness of being faulty, which, in turn, is calculated based on the execution behaviors of test cases. The performance of fault localization will deteriorate if the actual faulty statement is ranked low in suspiciousness. Intuitively speaking, the quality of the used test cases affects the suspiciousness ranking and thus the efficacy of fault localization. As such, it is necessary to generate test cases with “better” quality to improve the chance of faulty statements being ranked as highly suspicious. In this paper, we propose a software fault localization approach based on feedback ranking information, namely FLFR, according to an improved genetic algorithm. The starting point of the new method is the execution of a set of test cases, which gives a preliminary suspiciousness ranking of program statements. The improved genetic algorithm is iteratively applied to generate new test cases. The new method is evaluated through a series of experiments on four C programs and two Java programs. The experimental results show that the test cases automatically generated by the method can improve the suspiciousness ranking of the faulty statement, and thus enhance the performance of fault localization.
Funder
National Key R&D Program of China The Emergency Open Competition Project of National Forestry and Grassland Administration Outstanding Youth Team Project of Central Universities
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference52 articles.
1. Jones, J.A., Harrold, M.J., and Stasko, J.T. (2002, January 19–25). Visualization of test information to assist fault localization. Proceedings of the 24th International Conference on Software Engineering, Orlando, FL, USA. 2. Dallmeier, V., Lindig, C., and Zeller, A. (2005, January 19–21). Lightweight bug localization with AMPLE. Proceedings of the Sixth International Symposium on Automated Analysis-Driven Debugging, Monterey, CA, USA. 3. Santelices, R.A., Jones, J.A., Yu, Y., and Harrold, M.J. (2009, January 16). Lightweight fault-localization using multiple coverage types. Proceedings of the 2009 IEEE 31st International Conference on Software Engineering, Vancouver, BC, Canada. 4. Wong, W.E., Wei, T., Qi, Y., and Zhao, L. (2008, January 9–11). A Crosstab-based Statistical Method for Effective Fault Localization. Proceedings of the 2008 1st International Conference on Software Testing, Verification, and Validation, Lillehammer, Norway. 5. A Combinatorial Testing-Based Approach to Fault Localization;Ghandehari;IEEE Trans. Softw. Eng.,2020
|
|