Effort and Cost in Software Engineering

A Comparison of Two Industrial Data Sets

Conference Paper (2017)
Author(s)

H.K.M. Huijgens (TU Delft - Software Engineering)

Arie Deursen (TU Delft - Software Technology)

Leandro L. Minku (University of Leicester)

Chris Lokan (University of New South Wales)

Research Group
Software Engineering
Copyright
© 2017 H.K.M. Huijgens, A. van Deursen, Leandro L. Minku, Chris Lokan
DOI related publication
https://doi.org/10.1145/3084226.3084249
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 H.K.M. Huijgens, A. van Deursen, Leandro L. Minku, Chris Lokan
Research Group
Software Engineering
Pages (from-to)
51-60
ISBN (electronic)
978-1-4503-4804-1
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Context: The research literature on software development projects usually assumes that effort is a good proxy for cost. Practice, however, suggests that there are circumstances in which costs and effort should be distinguished. Objectives: We determine similar-ities and differences between size, effort, cost, duration, and num-ber of defects of software projects. Method: We compare two es-tablished repositories (ISBSG and EBSPM) comprising almost 700 projects from industry. Results: We demonstrate a (log)-linear relation between cost on the one hand, and size, duration and number of defects on the other. This justifies conducting linear regression for cost. We establish that ISBSG is substantially differ-ent from EBSPM, in terms of cost (cheaper) and duration (faster), and the relation between cost and effort. We show that while in ISBSG effort is the most important cost factor, this is not the case in other repositories, such as EBSPM in which size is the dominant factor. Conclusion: Practitioners and researchers alike should be cautious when drawing conclusions from a single repository.

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