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Quantitative Software Quality/Reliability Prediction Based on Project Management Data for Waterfall and Agile Development Paradigms

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Abstract

Software development productivity and product quality are related to quality of the software development process. Therefore, if we can improve quality of software development process based on project management technologies, software development productivity and product quality will be increased. In this paper, we conduct a multivariate analysis by using process measurement data, and derive a relational expression based on statistically significant factors, which can quantitatively predict final product quality/reliability. Furthermore, we apply a method of collaborative filtering by using process measurement data to predict final product quality from the similarity of software projects. Finally, we compare the results of two methods, i.e., multiple regression analysis and collaborative filtering, in terms of predictive accuracy of final product quality/reliability.

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Authors and Affiliations

  1. Department of Social Management Engineering, Graduate School of Engineering, Tottori University, 680-8552, Tottori-shi, Japan

    Shigeru Yamada & Toshiki Aoki

  2. Department of Information Systems, Faculty of Environmental and Information Studies, Tottori University of Environmental Studies Kita 1-1-1, 689-1111, Wakabadai, Tottori-shi, Japan

    Toshiyuki Toyota

Authors
  1. Shigeru Yamada
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  2. Toshiki Aoki
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  3. Toshiyuki Toyota
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Corresponding author

Correspondence to Shigeru Yamada.

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Yamada, S., Aoki, T. & Toyota, T. Quantitative Software Quality/Reliability Prediction Based on Project Management Data for Waterfall and Agile Development Paradigms. OPSEARCH 45, 391–404 (2008). https://doi.org/10.1007/BF03398828

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  • DOI: https://doi.org/10.1007/BF03398828

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