University of Minnesota
Software Engineering Center
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Critical Systems Research Group

The Critical Systems Research Group’s (CriSys) research interests are in the general area of software engineering; in particular, software development for critical software applications — applications where incorrect operation of the software could lead to loss of life, substantial material or environmental damage, or large monetary losses. The long-term goal of our research activities is the development of a comprehensive framework for the development of software for critical software systems. Our work has focused on some of the most difficult and least understood aspects of software development—requirements specification and validation/verification.

Recent Publications

Executing Model-based Tests on Platform-specific Implementations

Model-based testing of embedded real-time systems is challenging because platform-specific details are often abstracted away to make the models amenable to various analyses. Testing an implementation to expose non-conformance to such a model requires reconciling differences arising from these abstractions. Due to stateful behavior, naive comparisons of model and system behaviors often fail causing numerous false positives.

Automated Oracle Data Selection Support

The choice of test oracle—the artifact that determines whether an application under test executes correctly—can significantly impact the effectiveness of the testing process. However, despite the prevalence of tools that support test input selection, little work exists for supporting oracle creation. We propose a method of supporting test oracle creation that automatically selects the oracle data—the set of variables monitored during testing—for expected value test oracles.

Efficient Observability-based Test Generation by Dynamic Symbolic Execution

Structural coverage metrics have been widely used to measure test suite adequacy as well as to generate test cases. In previous investigations, we have found that the fault-finding effectiveness of tests satisfying structural coverage criteria is highly dependent on program syntax – even if the faulty code is exercised, its effect may not be observable at the output. To address these problems, observability-based coverage metrics have been defined.

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