| EPSRC Reference: |
GR/H90001/01 |
| Title: |
DEPENDIBILITY ASSESSMENT OF SCS THROUGH THE UNIFICATION OF MEASURABLE EVIDENCE (DATUM) IED4/1/9314 |
| Principal Investigator: |
Gollmann, Dr D |
| Other Investigators: |
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| Department: |
Computer Science |
| Organisation: |
Royal Holloway, Univ of London |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
24 May 1993 |
Ends: |
23 January 1997 |
Value (£): |
164,263
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| Information Technologies |
R&D |
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Summary on Grant Application Form |
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To advance the state of the art in assessing and predicting the dependability of systems by combining diverse sources of relevant information. A secondary objective is to help developers determine how different developers methods and system architectures contribute to the overall dependability argument. Progress:We have identified Bayesian probability as the most appropriate formalism for representing and combining evidence. We have analysed the contexts in which expert and Lay judgement is innaccurate or inconsistent. We have developed probability networks using the HUGIN tool as a key to rationalising combinations of evidence. This consistent Bayesian treatment of uncertainties based on full probabilistic dependence modelling provides a discipline against inconsistent probability assessments. We are applying generic human error models and our understanding of expert knowledge and behaviour to the assessment of risks stemming both from the design process and from human computer interaction during operation. We have formulated an approach to the role of formal methods in safety-critical systems design. Data collection, interviews, and protocol analysis are underway for both case studies. The project has benefited greatly from the very active involvement of Lloyds Register in both of the research themes and one of the case studies. Seventeen working papers have been produced, several of which have been published or submitted for publication. The following major issues have emerged: 1. Meaning of probability in dependability assessment.2. Bayesian models: (i) as dependability arguments in a safety case; (ii) to highlight potential process improvements3. How existing models of the software engineering/systems design process can be used to capture the contributions of formal methods in more detail.4. Taxonomy of errors and assessment methodologies.5. Difficulties of data collection6. Pragmatic solutions to a number of problems when using HUGIN.7. The role of multi-criteria decision theory and measurement theory.
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Key Findings |
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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