TY - GEN
T1 - DroidMutator
T2 - 42nd ACM/IEEE International Conference on Software Engineering: Companion, ICSE-Companion 2020
AU - Liu, Jian
AU - Xiao, Xusheng
AU - Xu, Lihua
AU - Dou, Liang
AU - Podgurski, Andy
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/10
Y1 - 2020/10
N2 - With the rapid growth of Android devices, techniques that ensure high quality of mobile applications (i.e., apps) are receiving more and more attention. It is well-accepted that mutation analysis is an effective approach to simulate and locate realistic faults in the program. However, there exist few practical mutation analysis tools for Android apps. Even worse, existing mutation analysis tools tend to generate a large number of mutants, hindering broader adoption of mutation analysis, let alone the remaining high number of stillborn mutants. Additionally, mutation operators are usually pre-defined by such tools, leaving users less ability to define specific operators to meet their own needs. To address the aforementioned problems, we propose DROIDMUTATOR, a mutation analysis tool specifically for Android apps with configurability and extensibility. DROIDMUTATOR reduces the number of generated stillborn mutants through type checking, and the scope of mutation operators can be customized so that it only generates mutants in specific code blocks, thus generating fewer mutants with more concentrated purposes. Furthermore, it allows users to easily extend their mutation operators. We have applied DROIDMUTATOR on 50 open source Android apps and our experimental results show that DROIDMUTATOR effectively reduces the number of stillborn mutants and improves the efficiency of mutation analysis.Demo link: Https://github.com/SQS-JLiu/DroidMutatorVideo link: Https://youtu.be/dtD0oTVioHM
AB - With the rapid growth of Android devices, techniques that ensure high quality of mobile applications (i.e., apps) are receiving more and more attention. It is well-accepted that mutation analysis is an effective approach to simulate and locate realistic faults in the program. However, there exist few practical mutation analysis tools for Android apps. Even worse, existing mutation analysis tools tend to generate a large number of mutants, hindering broader adoption of mutation analysis, let alone the remaining high number of stillborn mutants. Additionally, mutation operators are usually pre-defined by such tools, leaving users less ability to define specific operators to meet their own needs. To address the aforementioned problems, we propose DROIDMUTATOR, a mutation analysis tool specifically for Android apps with configurability and extensibility. DROIDMUTATOR reduces the number of generated stillborn mutants through type checking, and the scope of mutation operators can be customized so that it only generates mutants in specific code blocks, thus generating fewer mutants with more concentrated purposes. Furthermore, it allows users to easily extend their mutation operators. We have applied DROIDMUTATOR on 50 open source Android apps and our experimental results show that DROIDMUTATOR effectively reduces the number of stillborn mutants and improves the efficiency of mutation analysis.Demo link: Https://github.com/SQS-JLiu/DroidMutatorVideo link: Https://youtu.be/dtD0oTVioHM
KW - Android
KW - Mutation analysis
KW - Operators
UR - http://www.scopus.com/inward/record.url?scp=85098562384&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098562384&partnerID=8YFLogxK
U2 - 10.1145/3377812.3382134
DO - 10.1145/3377812.3382134
M3 - Conference contribution
AN - SCOPUS:85094113155
T3 - Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering: Companion, ICSE-Companion 2020
SP - 77
EP - 80
BT - Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 June 2020 through 19 July 2020
ER -