The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Don't touch my code!: examining the effects of ownership on software quality
Abstract
Ownership is a key aspect of large-scale software development. We examine the relationship between different ownership measures and software failures in two large software projects: Windows Vista and Windows 7. We find that in all cases, measures of ownership such as the number of low-expertise developers, and the proportion of ownership for the top owner have a relationship with both pre-release faults and post-release failures. We also empirically identify reasons that low-expertise developers make changes to components and show that the removal of low-expertise contributions dramatically decreases the performance of contribution based defect prediction. Finally we provide recommendations for source code change policies and utilization of resources such as code inspections based on our results.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 17,961
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Extreme Programming Explained: Embrace Change
Beck, K. L., & Andres, C. (2000) · Cited by 5,902
Random graphs with arbitrary degree distributions and their applications
Newman, M. E. J., Strogatz, S. H., & Watts, D. J. (2001) · Physical Review E · doi:10.1103/physreve.64.026118 · Cited by 3,648
Brooks, F. P. (1975) · ACM SIGPLAN Notices · doi:10.1145/390016.808439 · Cited by 3,224
The mythical man-month: essays on software engineering
(1996) · Choice Reviews Online · doi:10.5860/choice.33-5142 · Cited by 2,452
A critical point for random graphs with a given degree sequence
Molloy, M., & Reed, B. (1995) · Random Structures & Algorithms · doi:10.1002/rsa.3240060204 · Cited by 2,351
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
The Goal Question Metric Approach
Basili, V. R., Caldiera, G., & Rombach, H. D. (1994) · Cited by 1,651
Darr, E. D., Argote, L., & Epple, D. (1995) · Management Science · doi:10.1287/mnsc.41.11.1750 · Cited by 1,455
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
Curating GitHub for engineered software projects
Munaiah, N., Kroh, S., Cabrey, C., & Nagappan, M. (2017) · Empirical Software Engineering · doi:10.1007/s10664-017-9512-6 · Cited by 365
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
Progress on approaches to software defect prediction
Li, Z., Jing, X.-Y., & Zhu, X. (2018) · IET Software · doi:10.1049/iet-sen.2017.0148 · Cited by 264
An Empirical Study of Model-Agnostic Techniques for Defect Prediction Models
Jiarpakdee, J., Tantithamthavorn, C. K., Dam, H. K., & Grundy, J. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2020.2982385 · Cited by 148
Metadata
- Authors
- Bird, C., Nagappan, N., Murphy, B., Gall, H., & Devanbu, P.
- Venue
- Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
- Publisher
- ACM
- Published
- 2011-09-09
- Pages
- 4-14
- OpenAlex
- W2145574830
- Cited by
- 340
- References
- 40
- FWCI
- 13.94
- Type
- conference paper
- 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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Don't touch my code!: examining the effects of ownership on software quality. https://app.cochat.ai/papers/10.1145/2025113.2025119
- The paper
- Bird, C., Nagappan, N., Murphy, B., Gall, H., & Devanbu, P. (2011). Don't touch my code!: examining the effects of ownership on software quality. Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering. https://doi.org/10.1145/2025113.2025119
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.
