research-article

The effect of evolutionary coupling on software defects: an industrial case study on a legacy system

Authors:

Rasim MahmutogullariAuthors Info & Claims

ESEM '14: Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

Article No.: 6, Pages 1 - 7

https://doi.org/10.1145/2652524.2652577

Published: 18 September 2014 Publication History

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Abstract

Evolutionary coupling is defined as the implicit relationship between two or more software artifacts that are frequently changed together. In this study we investigate the effect of evolutionary coupling on defect proneness of a large financial legacy software in an industrial software development environment. We collected historical data for 5 years from 3 different software repositories containing 150 thousand files on 274 modules. Our results indicate that there is a positive correlation between evolutionary coupling and defect measures. Furthermore, we built linear and logistic regression models by using evolutionary coupling measures in order to explain defects. Although regression analysis results show that evolutionary coupling measures can be useful to explain defects, especially for modules in which high correlation is detected, explanatory power decreases dramatically with the decreasing correlation.

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Cited By

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Pisch ECai YKazman RLefever JFang H(2024)M-score: An Empirically Derived Software Modularity MetricProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686697(382-392)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686697
Sousa BBigonha MFerreira KFranco G(2024)Evolution of internal dimensions in object‐oriented software–A time series based approachSoftware: Practice and Experience10.1002/spe.331054:6(1034-1073)Online publication date: 21-Jan-2024
https://doi.org/10.1002/spe.3310
Zhong CZhang HLi CHuang HFeitosa D(2023)On measuring coupling between microservicesJournal of Systems and Software10.1016/j.jss.2023.111670200(111670)Online publication date: Jun-2023
https://doi.org/10.1016/j.jss.2023.111670
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Index Terms

The effect of evolutionary coupling on software defects: an industrial case study on a legacy system
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
2. Information systems
  1. Information systems applications

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Reviews

Reviewer: Bálint Molnár

What is the relationship between evolutionary coupling and software defects__?__ That is the research question raised in this paper. The scientific and empirical investigation of software development and its quality assurance has practical relevance. The evolutionary coupling concept captures the notion of entities of software systems that bear simultaneous impacts of modifications. Since the inception of original conceptualization, lots of advancement has occurred in management, software development techniques, and data analytics. The specific case study that is reported in this paper is a legacy, financial information system. The operation of the system follows the basic guidelines of the IT Infrastructure Library (ITIL), especially with respect to configuration management, source code handling, and defect tracking. During the life cycle of the particular system, plenty of data piled up. The availability of data mining software and the incorporated statistical packages provides an opportunity for analysis. Well-known correlation analysis, clustering, and logistic regression methods were used in the research. The outcome of the research conducted in this paper is that correlation can be demonstrated with some preconditions between the investigated parameters. The accurate measurement of data requires disciplined source code management. The results will be interesting to people who deal with the operational management of IT systems. From a research point of view, the paper contains quite a few new approaches; however, the conducted research can be considered as an accurate empirical investigation, exploiting the capability of recent statistical packages. The paper contributes to the scientific and empirical investigation of software development and operation, but can yield some clues for practitioners as well. Online Computing Reviews Service

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Published In

ESEM '14: Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

September 2014

461 pages

ISBN:9781450327749

DOI:10.1145/2652524

General Chair:
Maurizio Morisio
Politecnico di Torino, Italy
,
Program Chairs:
Tore Dybå
Sintef, Norway
,
Marco Torchiano
Politecnico di Torino, Italy

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 September 2014

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SIGSOFT

ESEM '14: 2014 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement

September 18 - 19, 2014

Torino, Italy

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ESEM '14 Paper Acceptance Rate 23 of 123 submissions, 19%;

Overall Acceptance Rate 130 of 594 submissions, 22%

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Cited By

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Pisch ECai YKazman RLefever JFang H(2024)M-score: An Empirically Derived Software Modularity MetricProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686697(382-392)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686697
Sousa BBigonha MFerreira KFranco G(2024)Evolution of internal dimensions in object‐oriented software–A time series based approachSoftware: Practice and Experience10.1002/spe.331054:6(1034-1073)Online publication date: 21-Jan-2024
https://doi.org/10.1002/spe.3310
Zhong CZhang HLi CHuang HFeitosa D(2023)On measuring coupling between microservicesJournal of Systems and Software10.1016/j.jss.2023.111670200(111670)Online publication date: Jun-2023
https://doi.org/10.1016/j.jss.2023.111670
Tuape MHasheela-Mufeti VIiyambo PKayanda AMensah SKasurinen J(2022)Software Practice in Small Software Companies: Development Context Constraints on Process Adoption.Proceedings of the 2022 European Symposium on Software Engineering10.1145/3571697.3571698(1-9)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1145/3571697.3571698
Tuape MHasheela-Mufeti VIiyambo PKayanda AKasirinen J(2021)Software Development Practice: How Organisation Dynamics Inhibit the Utilization of Process Tools in Small Software CompaniesProceedings of the 10th International Conference on Software and Information Engineering10.1145/3512716.3512722(35-40)Online publication date: 12-Nov-2021
https://dl.acm.org/doi/10.1145/3512716.3512722
Miholca DOnet-Marian Z(2020)An analysis of aggregated coupling's suitability for software defect prediction2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)10.1109/SYNASC51798.2020.00032(141-148)Online publication date: Sep-2020
https://doi.org/10.1109/SYNASC51798.2020.00032
Amaral LOliveira MLuz WFortes JBonifacio RAlencar DMonteiro EPinto GLo D(2020)How (Not) to Find Bugs: The Interplay Between Merge Conflicts, Co-Changes, and Bugs2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME46990.2020.00049(441-452)Online publication date: Sep-2020
https://doi.org/10.1109/ICSME46990.2020.00049
Rizwan MNadeem ASindhu M(2020)Empirical Evaluation of Coupling Metrics in Software Fault Prediction2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST)10.1109/IBCAST47879.2020.9044489(434-440)Online publication date: Jan-2020
https://doi.org/10.1109/IBCAST47879.2020.9044489
Mo RYin Z(2020)Exploring software bug-proneness based on evolutionary clique modeling and analysisInformation and Software Technology10.1016/j.infsof.2020.106380128(106380)Online publication date: Dec-2020
https://doi.org/10.1016/j.infsof.2020.106380
Zhou DWu YXiao LCai YPeng XFan JHuang LChen HGuéhéneuc YKhomh FSarro F(2019)Understanding evolutionary coupling by fine-grained co-change relationship analysisProceedings of the 27th International Conference on Program Comprehension10.1109/ICPC.2019.00046(271-282)Online publication date: 25-May-2019
https://dl.acm.org/doi/10.1109/ICPC.2019.00046
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Investigating the relationship between evolutionary coupling and software bug-proneness

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