Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62700
Title: Case-based reasoning for reducing software development effort
Authors: Brady, A
Menzies, T
Kocaguneli, E
Keung, J
Keywords: Software effort estimation
Case based reasoning
Effort estimation
Issue Date: 2011
Publisher: Scientific Research
Source: Journal of software engineering and applications, 2011, v. 3, no. 11, p. 1005-1014 How to cite?
Journal: Journal of software engineering and applications 
Abstract: How can we best find project changes that most improve project estimates? Prior solutions to this problem required the use of standard software process models that may not be relevant to some new project. Also, those prior solutions suffered from limited verification (the only way to assess the results of those studies was to run the recommendations back through the standard process models). Combining case-based reasoning and contrast set learning, the W system requires no underlying model. Hence, it is widely applicable (since there is no need for data to conform to some software process models). Also, W’s results can be verified (using holdout sets). For example, in the experiments reported here, W found changes to projects that greatly reduced estimate median and variance by up to 95% and 83% (respectively).
URI: http://hdl.handle.net/10397/62700
ISSN: 1945-3116 (print)
1945-3124 (online)
DOI: 10.4236/jsea.2010.311118
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