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Article

Mining Version Histories to Guide Software Changes

Authors:

Thomas Zimmermann,

Peter Weisgerber,

Andreas ZellerAuthors Info & Claims

ICSE '04: Proceedings of the 26th International Conference on Software Engineering

Pages 563 - 572

Published: 23 May 2004 Publication History

Abstract

We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed. . . ". Given a set of existing changes, such rules (a) suggest and predict likely further changes, (b) show up item coupling that is in detectable by program analysis, and (c) prevent errors due to incomplete changes. After an initial change, our ROSE prototype can correctly predict 26% of further files to be changed and 15% of the precise functions or variables.The topmost three suggestions contain a correct location with a likelihood of 64%.

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Cited By

Pérez FLapeña RMarcén ACetina C(2023)How the Quality of Maintenance Tasks is Affected by Criteria for Selecting Engineers for CollaborationACM Transactions on Software Engineering and Methodology10.1145/356138432:3(1-22)Online publication date: 26-Apr-2023
https://dl.acm.org/doi/10.1145/3561384
Navas-Su JGonzalez-Torres A(2022)An approach for the forecasting of the maintainability of system functionalitiesProceedings of the 2022 European Symposium on Software Engineering10.1145/3571697.3571702(33-42)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1145/3571697.3571702
Casamayor RArcega LPérez FCetina CSyriani ESahraoui H(2022)Bug localization in game software engineeringProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems10.1145/3550355.3552440(356-366)Online publication date: 23-Oct-2022
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Index Terms

Mining Version Histories to Guide Software Changes
1. Information systems
  1. Information systems applications
    1. Data mining
2. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software reverse engineering
      2. Software version control
  2. Software notations and tools
    1. Software configuration management and version control systems

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Published In

cover image ACM Conferences

ICSE '04: Proceedings of the 26th International Conference on Software Engineering

May 2004

761 pages

ISBN:0769521630

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

IEEE Computer Society

United States

Publication History

Published: 23 May 2004

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ICSE04

Sponsor:

SIGSOFT

ICSE04: 26th International Conference on Software Engineering

May 23 - 28, 2004

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ICSE '04 Paper Acceptance Rate 58 of 436 submissions, 13%;

Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Pérez FLapeña RMarcén ACetina C(2023)How the Quality of Maintenance Tasks is Affected by Criteria for Selecting Engineers for CollaborationACM Transactions on Software Engineering and Methodology10.1145/356138432:3(1-22)Online publication date: 26-Apr-2023
https://dl.acm.org/doi/10.1145/3561384
Navas-Su JGonzalez-Torres A(2022)An approach for the forecasting of the maintainability of system functionalitiesProceedings of the 2022 European Symposium on Software Engineering10.1145/3571697.3571702(33-42)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1145/3571697.3571702
Casamayor RArcega LPérez FCetina CSyriani ESahraoui H(2022)Bug localization in game software engineeringProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems10.1145/3550355.3552440(356-366)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550355.3552440
Arcega LFont JHaugen ØCetina C(2021)Bug Localization in Model-Based Systems in the WildACM Transactions on Software Engineering and Methodology10.1145/347261631:1(1-32)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3472616
Wu XZhu CLi YSpinellis DGousios GChechik MDi Penta M(2021)DIFFBASE: a differential factbase for effective software evolution managementProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3468264.3468605(503-515)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3468264.3468605
Chakroborti DRoy BNath S(2021)Designing for Recommending Intermediate States in A Scientific Workflow Management SystemProceedings of the ACM on Human-Computer Interaction10.1145/34571455:EICS(1-29)Online publication date: 29-May-2021
https://dl.acm.org/doi/10.1145/3457145
Grund FChowdhury SBradley NHall BHolmes R(2021)CodeShovelProceedings of the 43rd International Conference on Software Engineering10.1109/ICSE43902.2021.00135(1510-1522)Online publication date: 22-May-2021
https://dl.acm.org/doi/10.1109/ICSE43902.2021.00135
Wu XGrundy J(2021)Effectively analyzing evolving software with differential factsProceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE51524.2021.9678659(1064-1068)Online publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1109/ASE51524.2021.9678659
Mehta SBhagwan RKumar RBansal CMaddila CAshok BAsthana SBird CKumar ABhagwan RPorter G(2020)RexProceedings of the 17th Usenix Conference on Networked Systems Design and Implementation10.5555/3388242.3388274(435-448)Online publication date: 25-Feb-2020
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Menezes JTrindade BPimentel JMoura TPlastino AMurta LCosta CCavalcante EDantas FBatista T(2020)What causes merge conflicts?Proceedings of the XXXIV Brazilian Symposium on Software Engineering10.1145/3422392.3422440(203-212)Online publication date: 21-Oct-2020
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