Opinion is divided over the effectiveness of random testing. It produces test cases cheaply, but struggles with boundary conditions and is labour intensive without an automated oracle. We have created a search-based testing technique that evolves multiple sets of efficient subdomains, from which small but effective test suites can be randomly sampled. The new technique handles boundary conditions by targeting different mutants with each set of subdomains. It achieves an average 230% improvement in mutation score over conventional random testing.
|Name||Lecture Notes in Computer Science|
|Conference||5th International Symposium on Search Based Software Engineering|
|Period||24/08/13 → 26/08/13|