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Lian Duan

Lian Duan
Student/Research Assistant
External Links: 
http://www-users.cs.umn.edu/~lduan/
Education: 

BSEE 2006, Purdue University
MSEE 2007, Purdue University
Ph.D. student, University of Minnesota

Research: 
Software Engineering

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.

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.

Reasoning about Confidence and Uncertainty in Assurance Cases: A Survey

Assurance cases are structured logical arguments supported by evidence that explain how systems, possibly software systems, satisfy desirable properties for safety, security or reliability. The confidence in both the logical reasoning and the underlying evidence is a factor that must be considered carefully when evaluating an assurance case; the developers must have confidence in their case before the system is delivered and the assurance case reviewer, such as a regulatory body, must have adequate confidence in the case before approving the system for use.

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