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Cited by 550

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Towards a framework for software measurement validation

Kitchenham, B., Pfleeger, S.L., Fenton, N.·1995·IEEE Transactions on Software Engineering

Abstract

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.

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Metadata

Authors
Kitchenham, B., Pfleeger, S. L., & Fenton, N.
Venue
IEEE Transactions on Software Engineering
Published
1995
Volume
21
Issue
12
Pages
929-944
ISSN
0098-5589 (ISSN-L)
OpenAlex
W2161477496
Cited by
550
References
1
FWCI
44.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Towards a framework for software measurement validation. https://app.cochat.ai/papers/10.1109/32.489070
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Kitchenham, B., Pfleeger, S. L., & Fenton, N. (1995). Towards a framework for software measurement validation. IEEE Transactions on Software Engineering. https://doi.org/10.1109/32.489070

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.