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Details of Grant 

EPSRC Reference: EP/C005406/1
Title: eXdecide: Quantified Risk Assessment and Decision Support for Agile Software Projects
Principal Investigator: Fenton, Professor N
Other Investigators:
Neil, Professor M
Researcher Co-Investigators:
Dr W Marsh
Project Partners:
Agena Ltd
Department: Computer Science
Organisation: Queen Mary University of London
Scheme: Standard Research (Pre-FEC)
Starts: 14 March 2005 Ends: 13 March 2008 Value (£): 182,289
EPSRC Research Topic Classifications:
Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:  
Summary on Grant Application Form
Quantified risk management and assessment on software projects is primarily concerned with the need to predict and reason about trade-offs between resources, time, quality and functionality/scope. Despite the practical importance of this trade-off, little of the research on the subject has penetrated into practice. The two major reasons for this are that research has focused on: 1) Projects using 'heavyweight' development processes and a linear life-cycle; and2) Projects in which there is extensive data-collection and/or metrics programmes. Bitter experience has proved that few projects satisfy these criteria, with agile development processes (such as extreme programming, and lightweight UML) now the norm. The research challenge is therefore to provide quantitative risk assessment that can be tailored to suit any type of development process, with minimal assumptions about available data. Recent work in quantitative risk assessment using causal modelling (such as embodied in Bayesian nets) offers a potential solution. Bayesian Nets combine subjective and objective data to produce quantified measures of uncertainty even where there is incomplete data. If successful this project could revolutionise the way practitioners approach software risk, finally allowing sensible judgements about relevant trade-offs.
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