The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The influence of organizational structure on software quality: an empirical case study
Abstract
Often software systems are developed by organizations consisting of many teams of individuals working together. Brooks states in the Mythical Man Month book that product quality is strongly affected by organization structure. Unfortunately there has been little empirical evidence to date to substantiate this assertion. In this paper we present a metric scheme to quantify organizational complexity, in relation to the product development process to identify if the metrics impact failure-proneness. In our case study, the organizational metrics when applied to data from Windows Vista were statistically significant predictors of failure-proneness. The precision and recall measures for identifying failure-prone binaries, using the organizational metrics, was significantly higher than using traditional metrics like churn, complexity, coverage, dependencies, and pre-release bug measures that have been used to date to predict failure-proneness. Our results provide empirical evidence that the organizational metrics are related to, and are effective predictors of failure-proneness.
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Cites
Use of relative code churn measures to predict system defect density
Nagappan, N., & Ball, T. (2005) · Proceedings of the 27th international conference on Software engineering - ICSE '05 · doi:10.1145/1062455.1062514 · Cited by 775
Self-citationSplitting the organization and integrating the code: Conway's law revisited
Herbsleb, J. D., & Grinter, R. E. (1999) · Proceedings of the 21st international conference on Software engineering · doi:10.1145/302405.302455 · Cited by 425
People, organizations, and process improvement
Perry, D. E., Staudenmayer, N. A., & Votta, L. G. (1994) · IEEE Software · doi:10.1109/52.300082 · Cited by 401
Cited by
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
Tantithamthavorn, C., McIntosh, S., Hassan, A. E., & Matsumoto, K. (2017) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2584050 · Cited by 574
Software fault prediction metrics: A systematic literature review
Radjenović, D., Heričko, M., Torkar, R., & Živkovič, A. (2013) · Information and Software Technology · doi:10.1016/j.infsof.2013.02.009 · Cited by 538
Defect prediction from static code features: current results, limitations, new approaches
Menzies, T., Milton, Z., Turhan, B., Cukic, B., Jiang, Y., & Bener, A. (2010) · Automated Software Engineering · doi:10.1007/s10515-010-0069-5 · Cited by 466
An Empirical Study of RefactoringChallenges and Benefits at Microsoft
Kim, M., Zimmermann, T., & Nagappan, N. (2014) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2014.2318734 · Cited by 231
Self-citationBorg, M., Tornhill, A., & Mones, E. (2023) · Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering · doi:10.1145/3593434.3593480 · Cited by 18
Metadata
- Authors
- Nagappan, N., Murphy, B., & Basili, V.
- Venue
- Proceedings of the 13th international conference on Software engineering - ICSE '08
- Publisher
- ACM Press
- Published
- 2008
- Pages
- 521
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W2139855137
- Cited by
- 363
- References
- 3
- FWCI
- 18.89
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Nagappan, N., Murphy, B., & Basili, V. (2008). The influence of organizational structure on software quality: an empirical case study. Proceedings of the 13th international conference on Software engineering - ICSE '08. https://doi.org/10.1145/1368088.1368160
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