University of Minnesota
Software Engineering Center

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Oleg Sokolsky

Visiting Researcher

Recent Publications

Representation of Confidence in Assurance Cases using the Beta Distribution

Assurance cases are used to document an argument that a system---such as a critical software system---satisfies some desirable property (e.g., safety, security, or reliability). Demonstrating high confidence that the claims made based on an assurance case can be trusted is crucial to the success of the case. Researchers have proposed quantification of confidence as a Baconian probability ratio of eliminated concerns about the assurance case to the total number of identified concerns.

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.

Representation of Confidence in Assurance Case Evidence

When evaluating assurance cases, being able to capture the confidence one has in the individual evidence nodes is crucial, as these values form the foundation for determining the confidence one has in the assurance case as a whole. Human opinions are subjective, oftentimes with uncertainty---it is difficult to capture an opinion with a single probability value. Thus, we believe that a distribution best captures a human opinion such as confidence.