Using hardware testing approaches to improve software testing: Undetectable mutant identification

Over four decades of R&D has delivered near-universal automation of test generation for digital hardware. In contrast, software testing has limited automation and hence suffers from low test quality and high cost. One of the important reasons for this difference is that hardware ATPG is fault oriented. We note that the notion of a mutation in software testing is very similar to the notion of a fault in hardware testing, but current research on mutant oriented test generation for software is not extensive and the application is impeded by the scalability and undetectable mutant problems. This paper represents the first step in our identification of the similarities between software testing and hardware testing, and applying important insights from hardware testing to improve existing software mutant oriented testing. In particular, we propose the first approach for local analysis in software testing to identify mutants that are undetectable and demonstrate that our approach is effective and much more scalable than the state of the art.