TY - GEN
T1 - Is mutation analysis effective at testing android apps?
AU - Deng, Lin
AU - Offutt, Jeff
AU - Samudio, David
N1 - Publisher Copyright: © 2017 IEEE.
PY - 2017/8/11
Y1 - 2017/8/11
N2 - Not only is Android the most widely used mobile operating system, more apps have been released and downloaded for Android than for any other OS. However, quality is an ongoing problem, with many apps being released with faults, sometimes serious faults. Because the structure of mobile app software differs from other types of software, testing is difficult and traditional methods do not work. Thus we need different approaches to test mobile apps. In this paper, we identify challenges in testing Android apps, and categorize common faults according to fault studies. Then, we present a way to apply mutation testing to Android apps. Additionally, this paper presents results from two empirical studies on fault detection effectiveness using open-source Android applications: one for Android mutation testing, and another for four existing Android testing techniques. The studies use naturally occurring faults as well as crowdsourced faults introduced by experienced Android developers. Our results indicate that Android mutation testing is effective at detecting faults.
AB - Not only is Android the most widely used mobile operating system, more apps have been released and downloaded for Android than for any other OS. However, quality is an ongoing problem, with many apps being released with faults, sometimes serious faults. Because the structure of mobile app software differs from other types of software, testing is difficult and traditional methods do not work. Thus we need different approaches to test mobile apps. In this paper, we identify challenges in testing Android apps, and categorize common faults according to fault studies. Then, we present a way to apply mutation testing to Android apps. Additionally, this paper presents results from two empirical studies on fault detection effectiveness using open-source Android applications: one for Android mutation testing, and another for four existing Android testing techniques. The studies use naturally occurring faults as well as crowdsourced faults introduced by experienced Android developers. Our results indicate that Android mutation testing is effective at detecting faults.
KW - Android
KW - Crowdsourcing
KW - Empirical Evaluation
KW - Mutation Testing
KW - Software Testing
UR - https://www.scopus.com/pages/publications/85029448651
U2 - 10.1109/QRS.2017.19
DO - 10.1109/QRS.2017.19
M3 - Conference contribution
T3 - Proceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
SP - 86
EP - 93
BT - Proceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
Y2 - 25 July 2017 through 29 July 2017
ER -