Correlating Context-Awareness and Mutation Analysis for Pervasive Computing Systems

Pervasive computing systems often use middleware as a means to communicate with the changing environment. However, the interactions with the context-aware middleware as well as the interactions among applications sharing the same middleware may introduce faults that are difficult to reveal by existing testing techniques. Our previous work proposed the notion of context diversity as a metric to measure the degree of changes in test inputs for pervasive software. In this paper, we present a case study on how much context diversity for test cases relates to fault-based mutants in pervasive software. Our empirical results show that conventional mutation operators can generate sufficient candidate mutants to support test effectiveness evaluation of pervasive software, and test cases with higher context diversity values tend to have higher mean mutation scores. On the other hand, for test cases sharing the same context diversity, their mutation scores can vary significantly in terms of standard derivations.