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EPSRC Reference: GR/L37298/01
Title: NON-ALGORITHMIC METHODS OF ESTIMATION (NAME): AN EMPIRICAL INVESTIGATION INTO COST ESTIMATION TECHNIQUES
Principal Investigator: Shepperd, Professor M
Other Investigators:
Lefley, Dr M
Researcher Co-Investigators:
Project Partners:
Department: Sch of Design Engineering and Computing
Organisation: Bournemouth University
Scheme: Standard Research (Pre-FEC)
Starts: 01 January 1997 Ends: 31 December 1999 Value (£): 98,982
EPSRC Research Topic Classifications:
Software Engineering
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
Obtaining accurate estimates of effort at an early stage in software projects has long been a goal of researchers and software practitioners. To date most work has adopted an algorithmic approach either by utilising off the shelf models eg COCOMO or by statistically deriving models from local data. This has led to very mixed results. This research aims to explore a range of non traditional methods (analogy or case based reasoning, neural nets and fuzzy neural systems) for assisting in the prediction process. We have amassed eight industrial data sets (comprising over 200 completed software projects) for validating and comparing the various prediction methods. Siemens Plessey Systems will supply additional data from large projects and estimation expertise and will assist in the evaluation of the various methods. This will lead to the research's first deliverable, a comparison of the different production methods including, as a baseline, stepwise regression. It is expected that the suitability of different methods will depend upon the circumstances and that different methods can be complementary. Second, a set of guidelines will be developed to aid the choice and use of prediction methods. The third deliverable will be a PC based tool set to support the estimation process.
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Organisation Website: http://www.bmth.ac.uk