Testing pervasive software in the presence of context inconsistency resolution services

Pervasive computing software adapts its behavior according to the changing contexts. Nevertheless, contexts are often noisy. Context inconsistency resolution provides a cleaner pervasive computing environment to context-aware applications. A faulty context-aware application may, however, mistakenly mix up inconsistent contexts and resolved ones, causing incorrect results. This paper studies how such faulty context-aware applications may be affected by these services. We model how programs should handle contexts that are continually checked and resolved by context inconsistency resolution, develop novel sets of data flow equations to analyze the potential impacts, and thus formulate a new family of test adequacy criteria for testing these applications. Experimentation shows that our approach is promising.