TY - GEN
T1 - Improving Spectrum-Based Fault Localization using quality assessment and optimization of a test suite
AU - Liu, Chang
AU - Ma, Chunyan
AU - Zhang, Tao
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Spectral fault localization is an automatic fault-localization technique to expedite debugging, which uses risk evaluation formula to rank the risk of fault existence in each program entity after collecting testing information. To assess the potential usefulness of a test suite and improves the accuracy for spectral fault localization, methods of assessing and optimizing test suite are proposed in this paper, which. Firstly, Average Ranking Cost of the test suite quality and two kinds of constrains are defined; and test suite quality assessment method based on these definitions is given. Secondly, a new test suite optimization method based on greedy algorithm is proposed. Finally, two widely used program databases (SIR and Defects4j) and 8 SFL techniques are applied to verify the effectiveness of our method; and the fault localization cost before and after optimizing test suites of test objects are analyzed using effect size. The largest effect size reaches 0.5398 and Each SFL technology has different degrees of improvement in the rankings of faulty statements in different programs by optimizing test suite.
AB - Spectral fault localization is an automatic fault-localization technique to expedite debugging, which uses risk evaluation formula to rank the risk of fault existence in each program entity after collecting testing information. To assess the potential usefulness of a test suite and improves the accuracy for spectral fault localization, methods of assessing and optimizing test suite are proposed in this paper, which. Firstly, Average Ranking Cost of the test suite quality and two kinds of constrains are defined; and test suite quality assessment method based on these definitions is given. Secondly, a new test suite optimization method based on greedy algorithm is proposed. Finally, two widely used program databases (SIR and Defects4j) and 8 SFL techniques are applied to verify the effectiveness of our method; and the fault localization cost before and after optimizing test suites of test objects are analyzed using effect size. The largest effect size reaches 0.5398 and Each SFL technology has different degrees of improvement in the rankings of faulty statements in different programs by optimizing test suite.
KW - Average Ranking Cost
KW - Spectral fault localization
KW - Test suite quality assessment
UR - http://www.scopus.com/inward/record.url?scp=85099334606&partnerID=8YFLogxK
U2 - 10.1109/QRS-C51114.2020.00023
DO - 10.1109/QRS-C51114.2020.00023
M3 - 会议稿件
AN - SCOPUS:85099334606
T3 - Proceedings - Companion of the 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS-C 2020
SP - 72
EP - 78
BT - Proceedings - Companion of the 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS-C 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2020
Y2 - 11 December 2020 through 14 December 2020
ER -