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Article type: Research Article
Authors: Pendharkar, Parag C.
Affiliations: School of Business Administration, Pennsylvania State University at Harrisburg, 777 West Harrisburg Pike, Middletown, PA 17057, USA. Tel.: +1 717 948 6028; Fax: +1 717 948 6456; E-mail: [email protected]
Abstract: Recent research suggests that software testing consumes substantial resources and documenting source code is one way to reduce software maintenance cost. The software engineering literature provides little information on how to establish whether a software component is adequately documented. It appears that benchmarking can be used to identify a software component with little or no documentation. In this paper, we propose and illustrate how a hybrid Data Envelopment Analysis (DEA), Kohonen self-organizing mapping, and Euclidean distance based algorithm can be used to identify poorly documented software components.
Keywords: Data envelopment analysis, kohonen self organizing mapping, cluster analysis, software engineering, software maintenance
DOI: 10.3233/HIS-2009-0083
Journal: International Journal of Hybrid Intelligent Systems, vol. 6, no. 1, pp. 53-65, 2009
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