Generalized Coverage Criteria for Combinatorial Sequence Testing
This work addresses testing quality for software systems using combinatorial sequences, presenting an incremental improvement over previous approaches.
The paper tackles the problem of testing systems with sequences of actions by proposing generalized coverage criteria and a tool for generating high-quality test suites, resulting in demonstrated effectiveness in finding bugs and assessing risks.
We present a new model-based approach for testing systems that use sequences of actions and assertions as test vectors. Our solution includes a method for quantifying testing quality, a tool for generating high-quality test suites based on the coverage criteria we propose, and a framework for assessing risks. For testing quality, we propose a method that specifies generalized coverage criteria over sequences of actions, which extends previous approaches. Our publicly available tool demonstrates how to extract effective test suites from test plans based on these criteria. We also present a Bayesian approach for measuring the probabilities of bugs or risks, and show how this quantification can help achieve an informed balance between exploitation and exploration in testing. Finally, we provide an empirical evaluation demonstrating the effectiveness of our tool in finding bugs, assessing risks, and achieving coverage.