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Cited by 153Software Engineering ResearchSoftware Engineering Techniques and PracticesSoftware Reliability and Analysis Research

Code churn: a measure for estimating the impact of code change

Munson, J.C., Elbaum, S.G.·2002·Proceedings. International Conference on Software Maintenance (Cat. No. 98CB36272)
DOI 10.1109/icsm.1998.738486
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Abstract

This study presents a methodology that will produce a viable fault surrogate. The focus of the effort is on the precise measurement of software development process and product outcomes. Tools and processes for the static measurement of the source code have been installed and made operational in a large embedded software system. Source code measurements have been gathered unobtrusively for each build in the software evolution process. The measurements are synthesized to obtain the fault surrogate. The complexity of sequential builds is compared and a new measure, code churn, is calculated. This paper demonstrates the effectiveness of code complexity churn by validating it against the testing problem reports.

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Crossref · 10.1109/icsm.1998.738486

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  • Code churn is a widely recognized indicator of software maintainability.

    “Code churn is a widely recognized indicator of software maintainability [22].”

    From Self-Admitted GenAI Usage in Open-Source Software (2026) · cites this paper as [22]

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Authors
Munson, J. C., & Elbaum, S. G.
Affiliations
University of Idaho (US)
ORCID
Elbaum, S.G.
Venue
Proceedings. International Conference on Software Maintenance (Cat. No. 98CB36272)
Publisher
IEEE Comput. Soc
Published
2002-11-27
Pages
24-31
DOI
10.1109/icsm.1998.738486
OpenAlex
W2108161968
Cited by
153
References
0
Citations by year
2026: 4 · 2025: 6 · 2024: 2 · 2023: 3 · 2022: 6 · 2021: 9 · 2020: 7 · 2019: 7 · 2018: 7 · 2017: 10 · 2016: 2 · 2015: 6 · 2014: 15 · 2013: 9 · 2012: 10
FWCI
3.00
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Software Maintenance (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Research
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Physical Sciences › Computer Science › Software › Software Reliability and Analysis Research
Keywords
code churn, software complexity, static analysis, embedded software, software evolution, fault prediction, software testing

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