The DOI matches its Crossref record.
A General Empirical Solution to the Macro Software Sizing and Estimating Problem
Abstract
Application software development has been an area of organizational effort that has not been amenable to the normal managerial and cost controls. Instances of actual costs of several times the initial budgeted cost, and a time to initial operational capability sometimes twice as long as planned are more often the case than not.
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Citations
Cited by
Software Engineering Economics
Boehm, B. W. (2001) · Pioneers and Their Contributions to Software Engineering · doi:10.1007/978-3-642-48354-7_5 · Cited by 5,981
Understanding and controlling software costs
Boehm, B. W., & Papaccio, P. N. (1988) · IEEE Transactions on Software Engineering · doi:10.1109/32.6191 · Cited by 667
Clarke, P., & O’Connor, R. V. (2012) · Information and Software Technology · doi:10.1016/j.infsof.2011.12.003 · Cited by 332
Fenton, N. E., & Neil, M. (2000) · Proceedings of the Conference on The Future of Software Engineering · doi:10.1145/336512.336588 · Cited by 317
The 2017 IEEE International Conference on Fuzzy Systems
(2016) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2016.2545826 · Cited by 308
Metadata
- Authors
- Putnam, L. H.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 1978-07
- Volume
- SE-4
- Issue
- 4
- Pages
- 345-361
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2081004173
- Cited by
- 800
- References
- 0
- FWCI
- 41.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A General Empirical Solution to the Macro Software Sizing and Estimating Problem. https://app.cochat.ai/papers/10.1109/tse.1978.231521
- The paper
- Putnam, L. H. (1978). A General Empirical Solution to the Macro Software Sizing and Estimating Problem. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.1978.231521
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.