Issue No. 03 - March (1994 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/32.268921
<p>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 (E.J. Weyuker, 1988), but also show that a criticism of these properties by J.C. Cherniavsky and C.H. Smith (1991) 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.</p>
software metrics; measurement theory; programming theory; software measurement; scientific basis; measurement theory; software metrics work; metrics validation; software complexity measures; complexity attributes
N. Fenton, "Software Measurement: A Necessary Scientific Basis," in IEEE Transactions on Software Engineering, vol. 20, no. , pp. 199-206, 1994.