The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study
Abstract
Commercial software development is a complex task that requires a thorough understanding of the architecture of the software system. We analyze the Windows Server 2003 operating system in order to assess the relationship between its software dependencies, churn measures and post-release failures. Our analysis indicates the ability of software dependencies and churn measures to be efficient predictors of post-release failures. Further, we investigate the relationship between the software dependencies and churn measures and their ability to assess failure-proneness probabilities at statistically significant levels.
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Cites
A vector space model for automatic indexing
Salton, G., Wong, A., & Yang, C. S. (1975) · Communications of the ACM · doi:10.1145/361219.361220 · Cited by 7,521
A classification and comparison framework for software architecture description languages
Medvidovic, N., & Taylor, R. N. (2000) · IEEE Transactions on Software Engineering · doi:10.1109/32.825767 · Cited by 1,987
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-citation(2004) · doi:10.5555/998675.999432 · Cited by 656
Cited by
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
Software Defect Prediction via Convolutional Neural Network
Li, J., He, P., Zhu, J., & Lyu, M. R. (2017) · 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) · doi:10.1109/qrs.2017.42 · Cited by 462
Automation of systematic literature reviews: A systematic literature review
van Dinter, R., Tekinerdogan, B., & Catal, C. (2021) · Information and Software Technology · doi:10.1016/j.infsof.2021.106589 · Cited by 432
O’Mara-Eves, A., Thomas, J., McNaught, J., Miwa, M., & Ananiadou, S. (2015) · Systematic Reviews · doi:10.1186/s13643-015-0031-5 · Cited by 353
An empirical study of the impact of modern code review practices on software quality
McIntosh, S., Kamei, Y., Adams, B., & Hassan, A. E. (2016) · Empirical Software Engineering · doi:10.1007/s10664-015-9381-9 · Cited by 332
Metadata
- Authors
- Nagappan, N., & Ball, T.
- Venue
- First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007)
- Publisher
- IEEE
- Published
- 2007-09
- Pages
- 364-373
- ISSN
- 1938-6451 (ISSN-L)
- OpenAlex
- W2170207476
- Cited by
- 176
- References
- 4
- FWCI
- 4.60
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Nagappan, N., & Ball, T. (2007). Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study. First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007). https://doi.org/10.1109/esem.2007.13
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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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