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  1. Proceedings of the 10th International Conference on Predictive Models in Software Engineering (PROMISE '14)
  2. Feature weighting techniques for CBR in software effort estimation studies: a review and empirical evaluation
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A proposed method to evaluate and compare fault predictions across studies
Feature weighting techniques for CBR in software effort estimation studies: a review and empirical evaluation
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Feature weighting techniques for CBR in software effort estimation studies: a review and empirical evaluation

Content Provider ACM Digital Library
Author Sigweni, Boyce Shepperd, Martin
Abstract Context: Software effort estimation is one of the most important activities in the software development process. Unfortunately, estimates are often substantially wrong. Numerous estimation methods have been proposed including Case-based Reasoning (CBR). In order to improve CBR estimation accuracy, many researchers have proposed feature weighting techniques (FWT). Objective: Our purpose is to systematically review the empirical evidence to determine whether FWT leads to improved predictions. In addition we evaluate these techniques from the perspectives of (i) approach (ii) strengths and weaknesses (iii) performance and (iv) experimental evaluation approach including the data sets used. Method: We conducted a systematic literature review of published, refereed primary studies on FWT (2000--2014). Results: We identified 19 relevant primary studies. These reported a range of different techniques. 17 out of 19 make benchmark comparisons with standard CBR and 16 out of 17 studies report improved accuracy. Using a one-sample sign test this positive impact is significant (p = 0.0003). Conclusion: The actionable conclusion from this study is that our review of all relevant empirical evidence supports the use of FWTs and we recommend that researchers and practitioners give serious consideration to their adoption.
Starting Page 32
Ending Page 41
Page Count 10
File Format PDF
ISBN 9781450328982
DOI 10.1145/2639490.2639508
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-09-17
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Feature subset selection Case-based reasoning Software effort estimation Feature weighting Meta-analysis Systematic literature review
Content Type Text
Resource Type Article
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