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Towards a framework for software measurement validation
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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Cites
Measuring nominal scale agreement among many raters.
Fleiss, J. L. (1971) · Psychological Bulletin · doi:10.1037/h0031619 · Cited by 8,733
Cited by
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Bansiya, J., & Davis, C. G. (2002) · IEEE Transactions on Software Engineering · doi:10.1109/32.979986 · Cited by 1,020
An enhanced neural network technique for software risk analysis
Neumann, D. E. (2002) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2002.1033229 · Cited by 127
Automated reusability quality analysis of OO legacy software
Etzkorn, L. H., Hughes, W. E., & Davis, C. G. (2001) · Information and Software Technology · doi:10.1016/s0950-5849(00)00169-5 · Cited by 44
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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- 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).
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