Context driven environments are growing in popularity.Mobile applications, Internet of Things devices, autonomous vehicles, and future technologies respond to context events in their environments.This work uses a set of context events from real users to guide the generation of context driven test cases.Context event sequences are obtained by applying Conditional Random Fields (CRF).Test suites are then constructed by interleaving the context event sequences with GUI events.The choice of context event is made based on transitions obtained from the CRF.Results of the empirical studies show that techniques that incorporate context events provide better code coverage than NoContext for the subject applications.A heuristic technique introduced in this work, ISFreqOne, yields 4x better coverage than NoContext, 0.06x better coverage than Random Start Context, 0.05x better coverage than Iterative Start Context, which are control context generation techniques, and 0.04x better coverage than ISFreqTwo, another heuristic introduced in this work.

Mobile devices such as smart phones and smart watches utilize apps that run in context aware environments and must respond to context changes such as changes in network connectivity, battery level, screen orientation, and more.The large number of GUI events and context events often complicate the testing process.This work expands the AutoDroid tool to automatically generate tests that are guided by PairwiseInterleaved coverage of GUI event and context event sequences.We systematically weave context and GUI events into testing using the pairwise interleaved algorithm.The results show that the pairwise interleaved algorithm achieves up to five times higher code coverage compared to a technique that generates test suites in a single predefined context (without interleaving context and GUI events), a technique that changes the context at the beginning of each test case (without interleaving context and GUI events), and Monkey-Context-GUI (which randomly chooses context and GUI events).Future work will expand this strategy to include more context variables and test emerging technologies such as IoT and autonomous vehicles.