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Empirical Software Engineering

Erschienen in:

01.02.2012

A replicated assessment and comparison of adaptation techniques for analogy-based effort estimation

verfasst von: Mohammad Azzeh

Erschienen in: Empirical Software Engineering | Ausgabe 1-2/2012

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Abstract

Variants of adaptation techniques have been proposed in previous studies to improve the performance of analogy-based effort estimation. The results of these studies are often contradictory and cannot simply be generalized because there are many uncontrollable source of variations between adaptation studies. The study presented in this paper has been carried out in order to replicate the assessment and comparison of different adaptation techniques utilised in analogy-based software effort prediction. Empirical evaluation of variants of adaptation techniques with Jack-knifing procedure have been carried out. Seven datasets come from PROMISE data repository were used for benchmarking. The results are also investigated within the presence/absence of feature subset selection algorithm. The current study permitted us to discover that linear adjustment approaches are more accurate than nonlinear adjustment because of the nature of the employed datasets that have, in most cases, normality characteristics.

Vorheriger Artikel On the reproducibility of empirical software engineering studies based on data retrieved from development repositories

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All datasets used in this study are available on PROMISE website(http://www.promisedata.org)

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Titel: A replicated assessment and comparison of adaptation techniques for analogy-based effort estimation
verfasst von: Mohammad Azzeh
Publikationsdatum: 01.02.2012
Verlag: Springer US
Erschienen in: Empirical Software Engineering / Ausgabe 1-2/2012
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-011-9176-6

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