Proceedings of the 27th International Conference on Very Large Data Bases
Lowering the barriers to website testing with CoTester
Proceedings of the 15th international conference on Intelligent user interfaces
Proceedings of the 34th International Conference on Software Engineering
Efficient and change-resilient test automation: an industrial case study
Proceedings of the 2013 International Conference on Software Engineering
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In industrial practice, test cases often start out as steps described in natural language and are intended to be executed by a human. Since tests are executed repeatedly, they go through an automation process, in which they are converted to automated test scripts (or programs) that perform the test steps mechanically. Conventional test-automation techniques can be time-consuming, require specialized skills, and can produce fragile scripts. To address these limitations, we present a tool, called ata, for automating the test-automation task. Using a novel combination of natural-language processing, backtracking exploration, and learning, ata can significantly improve tester productivity in automating manual tests. ata also produces change-resilient scripts, which automatically adapt themselves in the presence of certain common types of user-interface changes.