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.

Pervasive context-aware software is an emerging kind of application. Many of these systems register parts of their context-aware logic in the middleware. On the other hand, most conventional testing techniques do not consider such kind of application logic. This paper proposes a novel family of testing criteria to measure the comprehensiveness of their test sets. It stems from context-aware data flow information. Firstly, it studies the evolution of contexts, which are environmental information relevant to an application program. It then proposes context-aware data flow associations and testing criteria. Corresponding algorithms are given. It uses a prototype testing tool to conduct experimentation on an RFID-based location sensing software running on top of context-aware middleware. The experimental results show that our approach is applicable, effective, and promising.

During the testing of context-sensitive middleware-based software, the middleware checks the current situation to invoke the appropriate functions of the applications. Since the middleware remains active and the situation may continue to evolve, however, the conclusion of some test cases may not easily be identified. Moreover, failures appearing in one situation may be superseded by subsequent correct outcomes and, therefore, be hidden. We alleviate the above problems by making use of a special kind of situation, which we call checkpoints, such that the middleware will not activate the functions under test. We recommend testers to generate test cases that start at a checkpoint and end at another. Testers may identify relations that associate different execution sequences of a test case. They then check the results of each test case to detect any contravention of such relations. We illustrate our technique with an example that shows how hidden failures can be detected. We also report the experimentation carried out on an RFID-based location-sensing application on top of a context-sensitive middleware.

Context-sensitive middleware-based software is an emerging kind of ubiquitous computing application. The components of such software communicate proactively among themselves according to the situational attributes of their environments, known as the "contexts". The actual process of accessing and updating the contexts lies with the middleware. The latter invokes the relevant local and remote operations whenever any context inscribed in the situation-aware interface is satisfied. Since the applications operate in a highly dynamic environment, the testing of context-sensitive software is challenging. Metamorphic testing is a property-based testing strategy. It recommends that, even if a test case does not reveal any failure, follow-up test cases should be further constructed from the original to check whether the software satisfies some necessary conditions of the problem to be implemented. This work proposes to use isotropic properties of contexts as metamorphic relations for testing context-sensitive software. For instance, distinct points on the same isotropic curve of contexts would entail comparable responses by the components. This notion of testing context relations is novel, robust, and intuitive to users.