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Improving Software Productivity
Abstract
This article discusses avenues of improving productivity for both custom and mass-produced software. Some of the topics covered are: The importance of improving software productivity, measuring software productivity, analyzing software productivity, improving and indicating trends in software productivity
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Citations
Cited by
A field study of the software design process for large systems
Curtis, B., Krasner, H., & Iscoe, N. (1988) · Communications of the ACM · doi:10.1145/50087.50089 · Cited by 2,076
Coordinating Expertise in Software Development Teams
Faraj, S., & Sproull, L. (2000) · Management Science · doi:10.1287/mnsc.46.12.1554.12072 · Cited by 1,689
Software developers' perceptions of productivity
Meyer, A. N., Fritz, T., Murphy, G. C., & Zimmermann, T. (2014) · Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering · doi:10.1145/2635868.2635892 · Cited by 224
The Work Life of Developers: Activities, Switches and Perceived Productivity
Meyer, A. N., Barton, L. E., Murphy, G. C., Zimmermann, T., & Fritz, T. (2017) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2017.2656886 · Cited by 170
Towards a Theory of Software Developer Job Satisfaction and Perceived Productivity
Storey, M.-A., Zimmermann, T., Bird, C., Czerwonka, J., Murphy, B., & Kalliamvakou, E. (2021) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2019.2944354 · Cited by 90
Metadata
- Authors
- Boehm
- Venue
- Computer
- Published
- 1987-09
- Volume
- 20
- Issue
- 9
- Pages
- 43-57
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2086306918
- Cited by
- 429
- References
- 0
- FWCI
- 57.46
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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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.
