Improving Test Adequacy and Software Reliability with Practices of Statistical Testing

Statistical testing based on a Markov chain usage model, as a rigorous testing method, has been around for more than two decades. Through the comprehensive application of statistical science to the testing of software, it provides audit trails of evidence to support correctness arguments for a software-intensive system as well as a decision that the system is of requisite quality for its intended use. This paper reports a real-world case study in which we applied standard statistical testing practices to the phone flag copy testing problem at the site of our industrial collaborator, and presents our solution from problem formalization, usage modeling and model analysis to test case generation and analysis. Our results helped evaluate the coverage of a heuristically generated test suite, and shed light on what other test cases to craft/generate to improve test coverage and adequacy, as well as reliability estimates both at the arc (usage event) level and at the path (system) level.