Analyzing clusters of web application user sessions

Abstract

User sessions provide valuable insight into the dynamic be- havior of web applications. They also play a key role in user-session-based testing, which gathers user sessions in the eld and replays selected sessions to test an evolving appli- cation. To decrease the testing and analysis e®ort, testers reduce the set of collected user sessions by either clustering user sessions by their shared URL attributes or by program coverage requirements-based reduction techniques. Cluster- ing URL attributes can be considerably less expensive; how- ever, the tradeo® may be that clustering is not representa-Tive of dynamic behavior similarities. This paper describes our analysis of user session data to reveal correlations be-Tween sessions clustered on the sessions' attributes and the relative dynamic behavior of the program for those sessions. The results of our analysis also motivate other clustering and test suite reduction techniques. Our results can also be used to learn more about how clusters of web application use cases are related in terms of the underlying user session attributes, program coverage, and fault detection.