Multi criteria selection of components using the analytic hierarchy process

  • Authors:

  • João W. Cangussu;Kendra C. Cooper;Eric W. Wong

  • Affiliations:

  • Department of Computer Science, University of Texas at Dallas, Richardson, TX;Department of Computer Science, University of Texas at Dallas, Richardson, TX;Department of Computer Science, University of Texas at Dallas, Richardson, TX

  • Venue:
  • CBSE'06 Proceedings of the 9th international conference on Component-Based Software Engineering
  • Year:
  • 2006

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Abstract

The Analytic Hierarchy Process (AHP) has been successfully used in the past for the selection of components, as presented in case studies in the literature. In this paper, an empirical study using AHP to rank components is presented. The components used in the study are for data compression; each implements one of the Arithmetic Encoding (AREC), Huffman coding (HUFF), Burrows-Wheeler Transform (BWT), Fractal Image Encoding (FRAC), and Embedded Zero-Tree Wavelet Encoder (EZW) algorithms. The ranking is a semi-automated approach that is based on using rigorously collected data for the components' behavior; selection criteria include maximum memory usage, total response time, and security properties (e.g., data integrity). The results provide a clear indication that AHP is appropriate for the task of selecting components when several criteria must be considered. Though the study is limited to select components based on multiple non-functional criteria, the approach can be expanded to include multiple functional criteria.