Improving analogy-based software cost estimation through probabilistic-based similarity measures

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

7 Scopus Citations
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Author(s)

  • Passakorn Phannachitta
  • Jacky Keung
  • Akito Monden
  • Ken-Ichi Matsumoto

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - Asia-Pacific Software Engineering Conference, APSEC
PublisherIEEE Computer Society
Pages541-546
Volume1
ISBN (Print)9781479921430, 9780769549224
Publication statusPublished - 2013

Publication series

Name
Volume1
ISSN (Print)1530-1362

Conference

Title20th Asia-Pacific Software Engineering Conference, APSEC 2013
PlaceThailand
CityBangkok
Period2 - 5 December 2013

Abstract

The performance of software cost estimation based on analogy reasoning depends upon the measures that specifying the similarity between software projects. This paper empirically investigates the use of probabilistic-based distance functions to improve the similarity measurement. The probabilistic-based distance functions are considerably more robust, because they collect the implicit correlation between the occurrences of project feature attributes. This information gain enables the constructed estimation model to be more concise and comprehensible. The study compares 6 probabilistic-based distance functions against the commonlyused Euclidian distance. We empirically evaluate the implemented cost estimation model using 5 real-world datasets collected from the PROMISE repository. The result shows a significant improvement in terms of error reduction, that implies an estimation based on probabilistic-based distance functions achieve higher accuracy on average, and the peak performance significantly outperforms the Euclidian distance based on Wilcoxon signed-rank test.

Research Area(s)

  • Analogy, Heterogeneous distance function, Machine learning, Software cost estimation

Citation Format(s)

Improving analogy-based software cost estimation through probabilistic-based similarity measures. / Phannachitta, Passakorn; Keung, Jacky; Monden, Akito; Matsumoto, Ken-Ichi.

Proceedings - Asia-Pacific Software Engineering Conference, APSEC. Vol. 1 IEEE Computer Society, 2013. p. 541-546 6805449.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review