A methodology for controlling the size of a test suite
ACM Transactions on Software Engineering and Methodology (TOSEM)
The use-case construct in object-oriented software engineering
Scenario-based design
On the inference of configuration structures from source code
ICSE '94 Proceedings of the 16th international conference on Software engineering
Reengineering class hierarchies using concept analysis
SIGSOFT '98/FSE-6 Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering
The concept of dynamic analysis
ESEC/FSE-7 Proceedings of the 7th European software engineering conference held jointly with the 7th ACM SIGSOFT international symposium on Foundations of software engineering
Improving web application testing with user session data
Proceedings of the 25th International Conference on Software Engineering
Debugging temporal specifications with concept analysis
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Types and Concept Analysis for Legacy Systems
IWPC '00 Proceedings of the 8th International Workshop on Program Comprehension
A Scalable Approach to User-Session based Testing of Web Applications through Concept Analysis
Proceedings of the 19th IEEE international conference on Automated software engineering
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User sessions provide valuable insight into the dynamic behavior of web applications. They also play a key role in user-session-based testing, which gathers user sessions in the field and replays selected sessions to test an evolving application. To decrease the testing and analysis effort, 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. Clustering URL attributes can be considerably less expensive; however, the tradeoff may be that clustering is not representative of dynamic behavior similarities. This paper describes our analysis of user session data to reveal correlations between 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.