DocumentCode :
3232286
Title :
Making resource decisions for software projects
Author :
Fenton, Norman ; Marsh, William ; Neil, Martin ; Cates, Patrick ; Forey, Simon ; Tailor, Manesh
Author_Institution :
Dept. of Comput. Sci., Univ. of London, UK
fYear :
2004
fDate :
23-28 May 2004
Firstpage :
397
Lastpage :
406
Abstract :
Software metrics should support managerial decision making in software projects. We explain how traditional metrics approaches, such as regression-based models for cost estimation fall short of this goal. Instead, we describe a causal model (using a Bayesian network) which incorporates empirical data, but allows it to be interpreted and supplemented using expert judgement. We show how this causal model is used in a practical decision-support tool, allowing a project manager to trade-off the resources used against the outputs (delivered functionality, quality achieved) in a software project. The model and toolset have evolved in a number of collaborative projects and hence capture significant commercial input. Extensive validation trials are taking place among partners on the EC funded project MODIST (this includes Philips, Israel Aircraft Industries and QinetiQ) and the feedback so far has been very good. The estimates are sensible and the causal modelling approach enables decision-makers to reason in a way that is not possible with other project management and resource estimation tools. To ensure wide dissemination and validation a version of the toolset with the full underlying model is being made available for free to researchers.
Keywords :
Bayes methods; decision support systems; estimation theory; public domain software; software development management; software metrics; Bayesian network; causal model; causal modelling; cost estimation; decision-support tool; empirical data; expert judgement; managerial decision making support; project MODIST; project management tools; regression-based models; resource decisions; resource estimation tools; software metrics; software projects; Bayesian methods; Collaborative tools; Costs; Decision making; Project management; Quality management; Resource management; Software metrics; Software quality; Software tools;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, 2004. ICSE 2004. Proceedings. 26th International Conference on
ISSN :
0270-5257
Print_ISBN :
0-7695-2163-0
Type :
conf
DOI :
10.1109/ICSE.2004.1317462
Filename :
1317462
Link To Document :
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