Comprehensive analysis of FBD test coverage criteria using mutants

Abstract

Function block diagram (FBD), a graphical modeling language for programmable logic controllers, has been widely used to implement safety critical system software such as nuclear reactor protection systems. With the growing importance of structural testing for FBD models, structural test coverage criteria for FBD models have been proposed and evaluated using mutation analysis in our previous work. We extend the previous work by comprehensively analyzing the relationships among fault detection effectiveness, test suite size, and coverage level through several research questions. We generate a large number of test suites achieving an FBD test coverage ranging from 0 to 100 %, and we also generate many artificial faults (i.e. mutants) for the FBD models. Our analysis results show that the fault detection effectiveness of the FBD coverage criteria increases with increasing coverage levels, and the coverage criteria are highly effective at detecting faults in all subject models. Furthermore, the test suites generated with the FBD coverage criteria are more effective and efficient than the randomly generated test suites. The FBD coverage criteria are strong at detecting faults in Boolean edges, while relatively weak at detecting wrong constants in FBD models. Empirical knowledge regarding our experiments provide the validity of using the FBD coverage criteria, and therefore, of FBD model-based testing.