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Mobile app testing is challenging since each test needs to be executed in a variety of operating contexts including heterogeneous devices, various wireless networks and different locations. Crowdsourcing enables a mobile app test to be distributed as a crowdsourced task to leverage crowd workers to accomplish the test. However, high test quality and expected test context coverage are difficult to...
Crowdsourced testing is an emerging trend in software testing, which relies on crowd workers to accomplish test tasks. Due to the cost constraint, a test task usually involves a limited number of crowd workers. Furthermore, more workers does not necessarily result in detecting more bugs. Different workers, who may have different testing experience and expertise, may make much differences in the test...
Mobile app testing is challenging since each test needs to be executed in a variety of operating contexts including heterogeneous devices, various wireless networks, and different locations. Crowdsourcing enables a mobile app testing to be distributed as a crowdsourced task to leverage the crowd in a community. However, a high test quality and expected test context coverage are difficult to achieve...
Symbolic execution is a systematic program analysis technique that has received a lot of attention in the research community. However, scaling symbolic execution continues to pose a major challenge. This paper introduces Synergise, a novel two-fold integration approach. One, it integrates distributed analysis and constraint re-use to enhance symbolic execution using feasible ranges, which allow sharing...
Mobile platform pervades human life, and much research in recent years has focused on improving the reliability of mobile applications on this platform, for example by applying automatic testing. However, researchers have primarily considered testing of single version of mobile applications. Although regression testing has been extensively studied for desktop applications, the approaches for desktop...
This tool paper presents a tool for performing memoized symbolic execution (Memoise), an approach we developed in previous work for more efficient application of symbolic execution. The key idea in Memoise is to allow re-use of symbolic execution results across different runs of symbolic execution without having to re-compute previously computed results as done in earlier approaches. Specifically,...
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