A similarity-aware approach to testing based fault localization Export

@inproceedings{citeulike:950560, abstract = {Debugging is a time-consuming task in software development and maintenance. To accelerate this task, several approaches have been proposed to automate fault localization. In particular, testing based fault localization (TBFL), which utilizes the testing information to localize the faults, seem to be very promising. However, the similarity between test cases in the test suite has been ignored in the research on TBFL. In this paper, we investigate this similarity issue and propose a novel approach named similarity-aware fault localization (SAFL), which can calculate the suspicion probability of each statement with little impact by the similarity issue. To address and deal with the similarity between test cases, SAFL applies the theory of fuzzy sets to remove the uneven distribution of the test cases. We also performed an experimental study for two real-world programs at different size levels to evaluate SAFL together with another two approaches to TBFL. Experimental results show that SAFL is more effective than the other two approaches when the test suites contain injected redundancy, and SAFL can achieve a competitive result with normal test suites. SAFL can also be more effective than applying test suite reduction to current approaches to TBFL.}, address = {New York, NY, USA}, author = {Hao, Dan and Pan, Ying and Zhang, Lu and Zhao, Wei and Mei, Hong and Sun, Jiasu}, booktitle = {ASE '05: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering}, citeulike-article-id = {950560}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1101908.1101953}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1101908.1101953}, doi = {10.1145/1101908.1101953}, isbn = {1595939934}, keywords = {debugging, sw\_engineering, testing}, pages = {291--294}, posted-at = {2006-11-17 22:50:36}, priority = {3}, publisher = {ACM Press}, title = {A similarity-aware approach to testing based fault localization}, url = {http://dx.doi.org/10.1145/1101908.1101953}, year = {2005} }

TY - CONF ID - citeulike:950560 L3 - citeulike-article-id:950560 N2 - Debugging is a time-consuming task in software development and maintenance. To accelerate this task, several approaches have been proposed to automate fault localization. In particular, testing based fault localization (TBFL), which utilizes the testing information to localize the faults, seem to be very promising. However, the similarity between test cases in the test suite has been ignored in the research on TBFL. In this paper, we investigate this similarity issue and propose a novel approach named similarity-aware fault localization (SAFL), which can calculate the suspicion probability of each statement with little impact by the similarity issue. To address and deal with the similarity between test cases, SAFL applies the theory of fuzzy sets to remove the uneven distribution of the test cases. We also performed an experimental study for two real-world programs at different size levels to evaluate SAFL together with another two approaches to TBFL. Experimental results show that SAFL is more effective than the other two approaches when the test suites contain injected redundancy, and SAFL can achieve a competitive result with normal test suites. SAFL can also be more effective than applying test suite reduction to current approaches to TBFL. SN - 1595939934 AD - New York, NY, USA EP - 294 TI - A similarity-aware approach to testing based fault localization PB - ACM Press T2 - ASE '05: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering SP - 291 KW - debugging KW - sw_engineering KW - testing AU - Hao, Dan AU - Pan, Ying AU - Zhang, Lu AU - Zhao, Wei AU - Mei, Hong AU - Sun, Jiasu PY - 2005/// UR - http://dx.doi.org/10.1145/1101908.1101953 ER -