TY - GEN
T1 - Improving Fault Localization by Complex-Fault Oriented Higher-Order Mutant Generation
AU - Chang, Zexing
AU - Liu, Yong
AU - Wu, Shumei
AU - Paul, Doyle
AU - Wang, Haifeng
AU - Chen, Xiang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Fault Localization (FL) is one of the most essential and time-consuming steps during software debugging. Mutation-based fault localization (MBFL) is one FL technique that has demonstrated promising fault localization accuracy in recent years. Current MBFL techniques mainly use First-Order Mutant (FOM) to localize faults, and only perform well in simple fault localization. When facing complex fault localization, MBFL with FOMs can only achieve low FL accuracy. Moreover, previous Higher-Order Mutant (HOM) generation techniques only use simple combinations of FOMs but do not consider the correlation between simple faults in the composition of complex faults. In this study, we consider the relationships between single faults and propose SFClu, a novel HOM generation method. Specifically, SFClu aims to generate HOMs to simulate complex faults consisting of multiple unrelated simple faults on multiple lines. To evaluate the performance of our proposed methods, we conduct empirical studies on 237 complex-fault programs from two datasets. The experimental results show that SFClu significantly outperforms traditional HOM generation methods (i.e., Last2First, DifferentOperators, and RandomMix). Furthermore, the experimental results also demonstrate that Higher-Order MBFL(HMBFL) with SFClu can outperform the state-of-the-art SBFL and MBFL techniques in terms of EXAM, TOP-N, and MAP metrics.
AB - Fault Localization (FL) is one of the most essential and time-consuming steps during software debugging. Mutation-based fault localization (MBFL) is one FL technique that has demonstrated promising fault localization accuracy in recent years. Current MBFL techniques mainly use First-Order Mutant (FOM) to localize faults, and only perform well in simple fault localization. When facing complex fault localization, MBFL with FOMs can only achieve low FL accuracy. Moreover, previous Higher-Order Mutant (HOM) generation techniques only use simple combinations of FOMs but do not consider the correlation between simple faults in the composition of complex faults. In this study, we consider the relationships between single faults and propose SFClu, a novel HOM generation method. Specifically, SFClu aims to generate HOMs to simulate complex faults consisting of multiple unrelated simple faults on multiple lines. To evaluate the performance of our proposed methods, we conduct empirical studies on 237 complex-fault programs from two datasets. The experimental results show that SFClu significantly outperforms traditional HOM generation methods (i.e., Last2First, DifferentOperators, and RandomMix). Furthermore, the experimental results also demonstrate that Higher-Order MBFL(HMBFL) with SFClu can outperform the state-of-the-art SBFL and MBFL techniques in terms of EXAM, TOP-N, and MAP metrics.
KW - Complex faults
KW - High-order mutants
KW - Mutation-based fault localization
UR - https://www.scopus.com/pages/publications/85168910980
U2 - 10.1109/COMPSAC57700.2023.00277
DO - 10.1109/COMPSAC57700.2023.00277
M3 - Conference contribution
AN - SCOPUS:85168910980
T3 - Proceedings - International Computer Software and Applications Conference
SP - 1792
EP - 1797
BT - Proceedings - 2023 IEEE 47th Annual Computers, Software, and Applications Conference, COMPSAC 2023
A2 - Shahriar, Hossain
A2 - Teranishi, Yuuichi
A2 - Cuzzocrea, Alfredo
A2 - Sharmin, Moushumi
A2 - Towey, Dave
A2 - Majumder, AKM Jahangir Alam
A2 - Kashiwazaki, Hiroki
A2 - Yang, Ji-Jiang
A2 - Takemoto, Michiharu
A2 - Sakib, Nazmus
A2 - Banno, Ryohei
A2 - Ahamed, Sheikh Iqbal
PB - IEEE Computer Society
T2 - 47th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2023
Y2 - 26 June 2023 through 30 June 2023
ER -