research-article

Build system analysis with link prediction

Authors:

Xin Xia,

David Lo,

Xinyu Wang,

Bo ZhouAuthors Info & Claims

SAC '14: Proceedings of the 29th Annual ACM Symposium on Applied Computing

Pages 1184 - 1186

https://doi.org/10.1145/2554850.2555134

Published: 24 March 2014 Publication History

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Abstract

Compilation is an important step in building working software system. To compile large systems, typically build systems, such as make, are used. In this paper, we investigate a new research problem for build configuration file (e.g., Makefile) analysis: how to predict missed dependencies in a build configuration file. We refer to this problem as dependency mining. Based on a Makefile, we build a dependency graph capturing various relationships defined in the Makefile. By representing a Makefile as a dependency graph, we map the dependency mining problem to a link prediction problem, and leverage 9 state-of-the-art link prediction algorithms to solve it. We collected Makefiles from 7 open source projects to evaluate the effectiveness of the algorithms.

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Cited By

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Lyu JLi SZhang HYang LLiu BRigger M(2024)Towards Efficient Build Ordering for Incremental Builds with Multiple ConfigurationsProceedings of the ACM on Software Engineering10.1145/36607741:FSE(1494-1517)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3660774
Lyu JLi SZhang HZhang YRong GRigger MChristakis MPradel M(2024)Detecting Build Dependency Errors in Incremental BuildsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652105(1-12)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3652105
Wu RChen MWang CFan GQiu JZhang C(2022)Accelerating Build Dependency Error Detection via Virtual BuildProceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering10.1145/3551349.3556930(1-12)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1145/3551349.3556930
Show More Cited By

Index Terms

Build system analysis with link prediction
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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Published In

SAC '14: Proceedings of the 29th Annual ACM Symposium on Applied Computing

March 2014

1890 pages

ISBN:9781450324694

DOI:10.1145/2554850

Conference Chairs:
Yookun Cho
Seoul National University, Korea
,
Sung Y. Shin
South Dakota State University
,
Program Chairs:
Sangwook Kim
Kyungpook National University, Korea
,
Chih-Cheng Hung
Southern Polytechnic State University
,
Jiman Hong
Soongsil University, South Korea

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2014

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Research-article

Funding Sources

National Natural Science Foundation of China
National Key Technology R&D Program of the Ministry of Science and Technology of China

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SAC 2014

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SIGAPP

SAC 2014: Symposium on Applied Computing

March 24 - 28, 2014

Gyeongju, Republic of Korea

Acceptance Rates

SAC '14 Paper Acceptance Rate 218 of 939 submissions, 23%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

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Lyu JLi SZhang HYang LLiu BRigger M(2024)Towards Efficient Build Ordering for Incremental Builds with Multiple ConfigurationsProceedings of the ACM on Software Engineering10.1145/36607741:FSE(1494-1517)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3660774
Lyu JLi SZhang HZhang YRong GRigger MChristakis MPradel M(2024)Detecting Build Dependency Errors in Incremental BuildsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652105(1-12)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3652105
Wu RChen MWang CFan GQiu JZhang C(2022)Accelerating Build Dependency Error Detection via Virtual BuildProceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering10.1145/3551349.3556930(1-12)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1145/3551349.3556930
Macho CBeyer SMcIntosh SPinzger M(2021)The nature of build changesEmpirical Software Engineering10.1007/s10664-020-09926-426:3Online publication date: 16-Mar-2021
https://doi.org/10.1007/s10664-020-09926-4
Fan GWang CWu RXiao XShi QZhang CKhurshid SPăsăreanu C(2020)Escaping dependency hell: finding build dependency errors with the unified dependency graphProceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3395363.3397388(463-474)Online publication date: 18-Jul-2020
https://dl.acm.org/doi/10.1145/3395363.3397388
Macho CMcIntosh SPinzger M(2018)Automatically repairing dependency-related build breakage2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER.2018.8330201(106-117)Online publication date: Mar-2018
https://doi.org/10.1109/SANER.2018.8330201
Macho CMcintosh SPinzger MGonzalez-Barahona JHindle ATan L(2017)Extracting build changes with BuildDiffProceedings of the 14th International Conference on Mining Software Repositories10.1109/MSR.2017.65(368-378)Online publication date: 20-May-2017
https://dl.acm.org/doi/10.1109/MSR.2017.65
Bezemer CMcintosh SAdams BGerman DHassan A(2017)An empirical study of unspecified dependencies in make-based build systemsEmpirical Software Engineering10.1007/s10664-017-9510-822:6(3117-3148)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s10664-017-9510-8
Macho CMcIntosh SPinzger M(2016)Predicting Build Co-changes with Source Code Change and Commit Categories2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)10.1109/SANER.2016.22(541-551)Online publication date: Mar-2016
https://doi.org/10.1109/SANER.2016.22
Zhou BXia XLo DWang X(2014)Build PredictorProceedings of the 2014 IEEE 38th Annual Computer Software and Applications Conference10.1109/COMPSAC.2014.12(53-58)Online publication date: 21-Jul-2014
https://dl.acm.org/doi/10.1109/COMPSAC.2014.12

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Accelerating Build Dependency Error Detection via Virtual Build

A sound and optimal incremental build system with dynamic dependencies

A sound and optimal incremental build system with dynamic dependencies

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