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Articles
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QICID: 24637
Title: Challenges of Data-Driven Cost Estimation in an Industrial Environment
Copyright: ASQ
Author: Heidrich, Jens; Trendowicz, Adam; Munch, Jurgen; Ishigai, Yasushi; Yokoyama, Kenyi; Kikuchi, Nahomi; Kawaguchi, T.
Organization: Fraunhofer IESE; IPA-SEC; Toshiba Information Systems Corp.
Subject: Software quality assurance (SQA); Software configuration management; Case study; Cost analysis; Lessons learned; Estimation; Data collection; Accuracy and precision;
Series: Software Quality Professional, Vol. 10, No. 4, September 2008, pp. 15-26
This ARTICLE is available FREE
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Abstract: [This abstract is based on the authors' abstract.]
Readily available data that allow companies to apply data-intensive estimation methods are often inconsistent, invalid, or incomplete. Most evaluation methods, with the exception of optimized set reduction (OSR®) cannot deal with imperfect data, and the results from evaluating these methods in practical environments are rare. A case study describes the application of OSR at Toshiba Information Systems Corporation. Results show that estimation accuracy varies with the data sets used and the manner of processing the data. The study supports current results in the area of quantitative cost estimation and illustrates typical problems. Lessons learned and recommendations are given.
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