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Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach

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  • Jeremiah D. Deng

    (University of Otago, New Zealand)

  • Martin Purvis

    (University of Otago, New Zealand)

  • Maryam Purvis

    (University of Otago, New Zealand)

Abstract

Software development effort estimation is important for quality management in the software development industry, yet its automation still remains a challenging issue. Applying machine learning algorithms alone often cannot achieve satisfactory results. This paper presents an integrated data mining framework that incorporates domain knowledge into a series of data analysis and modeling processes, including visualization, feature selection, and model validation. An empirical study on the software effort estimation problem using a benchmark dataset shows the necessity and effectiveness of the proposed approach.

Suggested Citation

  • Jeremiah D. Deng & Martin Purvis & Maryam Purvis, 2011. "Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 7(3), pages 41-53, July.
    • Handle: RePEc:igg:jiit00:v:7:y:2011:i:3:p:41-53
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