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In this paper we propose a framework for validating software measurement. We start by defining a measurement structure model that identifies the elementary component of measures and the measurement process, and then consider five other models involved in measurement: unit definition models, instrumentation models, attribute relationship models, measurement protocols and entity population models. We consider a number of measures from the viewpoint of our measurement validation framework and identify a number of shortcomings; in particular we identify a number of problems with the construction of function points. We also compare our view of measurement validation with ideas presented by other researchers and identify a number of areas of disagreement. Finally, we suggest several rules that practitioners and researchers can use to avoid measurement problems, including the use of measurement vectors rather than artificially contrived scalars.
Measurement theory, software measurement, software metrics validation.

N. Fenton, B. Kitchenham and S. L. Pfleeger, "Towards a Framework for Software Measurement Validation," in IEEE Transactions on Software Engineering, vol. 21, no. , pp. 929-944, 1995.
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