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Faculty of Graduate Studies

Simon Diemert

  • B.Engr., (University of Victoria, 2015)

  • MSc (University, 2017)

Notice of the Final Oral Examination for the Degree of Doctor of Philosophy

Topic

Confidence in Dynamic Assurance Cases

Department of Computer Science

Date & location

  • Friday, May 1, 2026

  • 9:00 A.M.

  • Engineering Office Wing, Room 230

  • and Virtual Defence

Reviewers

Supervisory Committee

  • Dr. Jens Weber, Department of Computer Science, University of Victoria (Supervisor)

  • Dr. Hausi Müller, Department of Computer Science, UVic (Member)

  • Dr. Issa Traore, Department of Electrical and Computer Engineering, UVic (Outside Member) 

External Examiner

  • Dr. Alan Wassyng, Department of Computer and Software, McMaster University 

Chair of Oral Examination

  • Dr. Malcolm Gaston, School of Public Administration, UVic 

     

Abstract

Assuring safety- and security-critical systems is a necessary activity, both prior to deployment (at “design-time”) and during system operation (at “run-time”). The need for assurance is heightened as these systems increasingly depend on artificial intelligence and adaptation strategies to handle uncertainty in their operating environments. Assurance Cases (ACs) that incorporate structured arguments and supporting evidence are an important tool for establishing trust in critical systems. Mod ern ACs are not static documents: they are increasingly viewed as dynamic models of “through-life” assurance and are used for decision-making at both design- and run-time. These Dynamic Assurance Cases (DACs) incorporate dynamic sources of evidence and “live” data from development activities or operations (e.g., safety performance indicators). However, a question arises during their use: “are we confident in the claim(s) made by this version of the case?”

While several methods exist to assess confidence in ACs, there is limited knowledge about their adoption by practitioners. Additionally, there are several limitations of quantitative methods, including: 1) an inability to consider the impact of dynamic aspects on confidence; 2) an inability to account for dialectic reasoning (i.e., “defeaters”); and 3) challenges related to subjectivity, interpretability, precision, and modelling nuanced reasoning. The overall objective of this work is to develop a new confidence assessment method that is grounded in the needs of practitioners and addresses the limitations mentioned above.

Towards this objective, the main contribution of this dissertation is a new mixed (qualitative and quantitative) method for AC confidence assessment called Certus. Confidence in an AC is modelled using vague, but linguistically meaningful expressions (e.g., “I have very high belief that this claim is true”). A domain specific language is used to describe belief propagation through a structured argument to produce an overall belief valuation for the AC. Certus supports dialectic reasoning and can condition belief assessments on the availability of evidence and the value of performance indicators. The use of the language is guided by a methodology that integrates with the existing practices for developing (D)ACs. A denotational semantics for the language provides a formal basis for assessment. The language and method are evaluated through a series of analyses and a case study to demonstrate that they possess properties related to trustworthiness, including: stability in propagation, sensitivity, expressivity, scalability, and applicability to DACs.

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