Prioritizing test suites by finding Hamiltonian paths: Preliminary studies and initial results

This paper describes a technique for prioritizing a test suite by finding the least weight Hamiltonian path in a complete graph that represents relative testing costs. Our technique is especially useful when testing confronts constraints such as quotas in a Web service, memory overhead, or test execution time. During the testing of modern mobile computing devices (e.g., handsets running Google Android), it is often challenging to properly handle memory constraints. Thus, even though we anticipate that our approach is valuable in a wide variety of limited resource environments, this paper focuses on prioritizing test suites for memory constrained execution.