Clustering and Tailoring User Session Data for Testing Web Applications

Web applications have become major driving forces for world business. Effective and efficient testing of evolving web applications is essential for providing reliable services. In this paper, we present a user session based testing technique that clusters user sessions based on the service profile and selects a set Of representative user sessions from each cluster. Then each selected user session is tailored by augmentation with additional requests to cover the dependence relationships between web pages. The created test suite not only can significantly reduce the size of the collected user sessions, but is also viable to exercise fault sensitive paths. We conducted two empirical studies to investigate the effectiveness of our approach-one one was in a controlled environment using seeded faults, and the other was conducted on an industrial system with real faults. The results demonstrate that our approach consistently detected the majority of the known faults by using a relatively small number of test cases in both studies.