Detecting, Isolating and Enforcing Dependencies Between and Within Test Cases

Testing stateful applications is challenging, as it can be difficult to identify hidden dependencies on program state. These dependencies may manifest between several test cases, or simply within a single test case. When it’s left to developers to document, understand, and respond to these dependencies, a mistake can result in unexpected and invalid test results. Although current testing infrastructure does not currently leverage state dependency information, we argue that it could, and that by doing so testing can be improved. Our results thus far show that by recovering dependencies between test cases and modifying the popular testing framework, JUnit, to utilize this information, we can optimize the testing process, reducing time needed to run tests by 62% on average. Our ongoing work is to apply similar analyses to improve existing state of the art test suite prioritization techniques and state of the art test case generation techniques. This work is advised by Professor Gail Kaiser.