Fail-Safe Testing of Web Applications

This paper proposes a genetic algorithm (GA)method to generate test scenarios for testing proper fail-safe behavior for web applications. Unlike other approaches which combine fault trees with state charts, we create mitigation tests from an existing functional black box test suite. A genetic algorithm is used that determines points of failures and type of failure that need to be tested. Mitigation test paths are woven into the behavioral test at the point of failure based on failure specific weaving rules. The GA approach is compared to random selection. We also provide experimental results how effectiveness and efficiency vary based on mitigation defect density and length of the test suite.