Abstract
Software measurement, like measurement in any other discipline, must adhere to the science of measurement if it is to gain widespread acceptance and validity. The observation of some very simple, but fundamental, principles of measurement can have an extremely beneficial effect on the subject. Measurement theory is used to highlight both weaknesses and strengths of software metrics work, including work on metrics validation. We identify a problem with the well known Weyuker properties, but also show that a criticism of these properties by Cherniaysky and Smith is invalid. We show that the search for general software complexity measures is doomed to failure. However, the theory does help us to define and validate measures of specific complexity attributes. Above all, we are able to view software measurement in a very wide perspective, rationalising and relating its many diverse activities.
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© 1995 ECSC — EC — EAEC, Brussels — Luxembourg
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Fenton, N.E. (1995). Software Measurement: A Necessary Scientific Basis. In: Randell, B., Laprie, JC., Kopetz, H., Littlewood, B. (eds) Predictably Dependable Computing Systems. ESPRIT Basic Research Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79789-7_5
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DOI: https://doi.org/10.1007/978-3-642-79789-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-79791-0
Online ISBN: 978-3-642-79789-7
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