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Details of Grant 

EPSRC Reference: GR/L06683/01
Title: IMPRESS: IMPROVING THE SOFTWARE PROCESS USING BAYESIAN NETS
Principal Investigator: Neil, Professor M
Other Investigators:
Littlewood, Professor B Strigini, Professor L Fenton, Professor N
Researcher Co-Investigators:
Project Partners:
Hugin Expert A/S
Department: Computing Science
Organisation: City, University of London
Scheme: Standard Research (Pre-FEC)
Starts: 13 January 1997 Ends: 28 March 2000 Value (£): 226,714
EPSRC Research Topic Classifications:
Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:  
Summary on Grant Application Form
This project builds on successful and novel research developed within the centre for Software Reliability that allows us to express quantitative arguments about the safety and dependability properties of software-based systems. We have used Bayesian Belief Networks (BBNs) and decision analysis techniques to integrate software process and product evidence in order to predict the future dependability of a system. While this work has obvious (and well-accepted) relevance to the safety-critical community, we believe it can have the greatest impact in mainstream software engineering (including the commercial sector). This massive community continues to rely on ill-conceived, ad-hoc methods for assessing the quality of their processes and products. We plan to integrate BBNs and decision analysis techniques with the techniques associated with high-levels of process maturity: defect analysis, quality modelling and statistical process control. In doing this, current approaches to software quality control and measurement will be significantly enhanced. This work will also address future implementation and exploitation by producing a demonstration prototype to make the technology more accessible to software quality managers than the dry mathematics in which it is currently formulated.
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Organisation Website: http://www.city.ac.uk