A review and comparison of methods for determining the best analogies in analogy-based software effort estimation

Bodin Chinthanet, Pattara Leelaprute, Arnon Rungsawang, Passakorn Phannachitta, Naoyasu Ubayashi, Yasutaka Kamei, Kenichi Matsumoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Analogy-based effort estimation (ABE) is a commonly used software development effort estimation method. The processes of ABE are based on a reuse of effort values from similar past projects, where the appropriate numbers of past projects (k values) to be reused is one of the long-standing debates in ABE research studies. To date, many approaches to find this k value have been continually proposed. One important reason for this inconclusive debate is that different studies appear to produce different conclusions of the k value to be appropriate. Therefore, in this study, we revisit 8 common approaches to the k value being most appropriate in general situations. With a more robust and comprehensive evaluation methodology using 5 robust error measures subject to the Wilcoxon rank-sum statistical test, we found that conflicting results in the previous studies were not mainly due to the use of different methodologies nor different datasets, but the performance of the different approaches are actually varied widely.

Original languageEnglish
Title of host publication2016 Symposium on Applied Computing, SAC 2016
PublisherAssociation for Computing Machinery
Pages1554-1557
Number of pages4
ISBN (Electronic)9781450337397
DOIs
Publication statusPublished - Apr 4 2016
Event31st Annual ACM Symposium on Applied Computing, SAC 2016 - Pisa, Italy
Duration: Apr 4 2016Apr 8 2016

Publication series

NameProceedings of the ACM Symposium on Applied Computing
Volume04-08-April-2016

Other

Other31st Annual ACM Symposium on Applied Computing, SAC 2016
CountryItaly
CityPisa
Period4/4/164/8/16

All Science Journal Classification (ASJC) codes

  • Software

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