Data-Driven Mutation Analysis for Cyber-Physical Systems

Cyber-physical systems (CPSs) typically consist of a wide set integrated, heterogeneous components; consequently, most their critical failures relate to the interoperability such components. Unfortunately, CPS test automation techniques are preliminary and industry still heavily relies on manual testing. With potentially incomplete, manually-generated suites, it is paramount importance assess quality. Though mutation analysis has demonstrated be an effective means suite quality in some specific contexts, we lack approaches for CPSs. Indeed, existing do not target problems cannot executed presence black-box or simulated components, typical situation with In this article, introduce data-driven analysis , approach that consists assessing by verifying if detects faults mutating data exchanged software To end, describe data-driven technique ( xmlns:xlink="http://www.w3.org/1999/xlink">DaMAT ) automatically alters through buffers. Our driven fault models tabular form where engineers specify how mutate items selecting configuring operators. We have evaluated CPSs space domain; specifically, suites microsatellite nanosatellites launched orbit last year. results show effectively shortcomings, affected equivalent redundant mutants, entails acceptable costs.