| EPSRC Reference: |
GR/N00258/01 |
| Title: |
SCULLY SCALLING UP BAYESIAN NETS FOR SOFTWARE RISK ASSESSMENT |
| Principal Investigator: |
Fenton, Professor N |
| Other Investigators: |
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| Department: |
Computer Science |
| Organisation: |
Queen Mary University of London |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
13 July 2000 |
Ends: |
12 July 2003 |
Value (£): |
203,501
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| EPSRC Industrial Sector Classifications: |
| Electronics |
Information Technologies |
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Summary on Grant Application Form |
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ayesian Belief nets (BBNs) provide an ideal framework for software risk assessment and process improvement. Unlike traditional metrics approaches, BBNs can incorporate a range of metrics into a causal model of the software development and testing process. Hence, BBNs provide more accurate Predictions of critical attributes (like cost and quality) than can be achieved by traditional -egression approaches. However, although the breakthrough BBN algorithms of the 1980's finally enabled large BBNs to be EXECUTED, there was little support until very recently for the problems of BUILDING large-scale BBNs. In our own recent projects we have made major technological advances in this area that have enabled us to build real application domain solutions (in the general area of software dependability/ quality) on an unprecedented scale. These applications, however, require significant expert involvement and are not easily tailorable, while the process of using the methods and tools requires highly specialised skills. Hence, this proposal aims to move the process of building large-scale BBNs on to the next evolutionary level. We will develop methods to remove the remaining technological barriers that prevent non-experts from building and using large-scale BBNs. An active User group of existing industrial contacts will validate the methods.
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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 |
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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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