TY - GEN
T1 - Model-based testing of end-user collaboration intensive systems
AU - Gambi, Alessio
AU - Mayr-Dorn, Christoph
AU - Zeller, Andreas
N1 - Funding Information:
The authors would like to thank Filip Rydzi for providing the code of the social network. This work was funded by an European Research Council (ERC) Advanced Grant "SPECMATE - Specification Mining and Testing" and supported by the Austrian Science Fund (FWF): P29415-NBL funded by the Government of Upper Austria.
Publisher Copyright:
© 2017 ACM.
PY - 2017/4/3
Y1 - 2017/4/3
N2 - Collaboration intensive systems like social networks support the interaction of multiple end-users playing different roles such as "friend" or "post owner". To ensure that end-users achieve the intended type of collaboration, systematic testing can be an effective means. However, manually creating effective test cases is cumbersome and error prone as the amount of end-users interactions to test grows exponentially with the number of involved end-users and roles. In this paper, we present a novel approach for automatic test case generation via modeling user collaborations as synchronized, non-deterministic Finite State Machines. As our preliminary evaluation shows, such collaboration models are effective and efficient: compared to collaboration-unaware alternatives, we generated test cases which achieve higher code coverage and trigger more errors, up to 10× faster.
AB - Collaboration intensive systems like social networks support the interaction of multiple end-users playing different roles such as "friend" or "post owner". To ensure that end-users achieve the intended type of collaboration, systematic testing can be an effective means. However, manually creating effective test cases is cumbersome and error prone as the amount of end-users interactions to test grows exponentially with the number of involved end-users and roles. In this paper, we present a novel approach for automatic test case generation via modeling user collaborations as synchronized, non-deterministic Finite State Machines. As our preliminary evaluation shows, such collaboration models are effective and efficient: compared to collaboration-unaware alternatives, we generated test cases which achieve higher code coverage and trigger more errors, up to 10× faster.
KW - Finite state machine
KW - Model-driven testing
UR - http://www.scopus.com/inward/record.url?scp=85020898999&partnerID=8YFLogxK
U2 - 10.1145/3019612.3019778
DO - 10.1145/3019612.3019778
M3 - Conference contribution
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 1213
EP - 1218
BT - 32nd Annual ACM Symposium on Applied Computing, SAC 2017
A2 - Seffah, Ahmed
A2 - Penzenstadler, Birgit
A2 - Alves, Carina
A2 - Peng, Xin
PB - ACM
ER -