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Innovations in Systems and Software Engineering
Erschienen in: Innovations in Systems and Software Engineering 4/2014

01.12.2014 | Original Paper

A statistical study of the relevance of lines of code measures in software projects

verfasst von: Adrian S. Barb, Colin J. Neill, Raghvinder S. Sangwan, Michael J. Piovoso

Erschienen in: Innovations in Systems and Software Engineering | Ausgabe 4/2014

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Abstract

Lines of code metrics are routinely used as measures of software system complexity, programmer productivity, and defect density, and are used to predict both effort and cost. The guidelines for using a direct metric, such as lines of code, as a proxy for a quality factor such as complexity or defect density, or in derived metrics such as cost and effort are clear. Amongst other criteria, the direct metric must be linearly related to, and accurately predict, the quality factor and these must be validated through statistical analysis following a rigorous validation methodology. In this paper, we conduct such an analysis to determine the validity and utility of lines of code as a measure using the ISBGS-10 data set. We find that it fails to meet the specified validity tests and, therefore, has limited utility in derived measures.
Vorheriger Artikel State of practice in requirements engineering: contemporary data
Nächster Artikel Multi-objective test prioritization via a genetic algorithm

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Metadaten
Titel
A statistical study of the relevance of lines of code measures in software projects
verfasst von
Adrian S. Barb
Colin J. Neill
Raghvinder S. Sangwan
Michael J. Piovoso
Publikationsdatum
01.12.2014
Verlag
Springer London
Erschienen in
Innovations in Systems and Software Engineering / Ausgabe 4/2014
Print ISSN: 1614-5046
Elektronische ISSN: 1614-5054
DOI
https://doi.org/10.1007/s11334-014-0231-5

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