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A sentence-matching method for automatic license identification of source code files

Authors:

Daniel M. German,

Katsuro InoueAuthors Info & Claims

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

Pages 437 - 446

https://doi.org/10.1145/1858996.1859088

Published: 20 September 2010 Publication History

Abstract

The reuse of free and open source software (FOSS) components is becoming more prevalent. One of the major challenges in finding the right component is finding one that has a license that is e for its intended use. The license of a FOSS component is determined by the licenses of its source code files. In this paper, we describe the challenges of identifying the license under which source code is made available, and propose a sentence-based matching algorithm to automatically do it. We demonstrate the feasibility of our approach by implementing a tool named Ninka. We performed an evaluation that shows that Ninka outperforms other methods of license identification in precision and speed. We also performed an empirical study on 0.8 million source code files of Debian that highlight interesting facts about the manner in which licenses are used by FOSS

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Cited By

Katzy JPopescu RVan Deursen AIzadi MLo DPenta MXia XHu X(2024)An Exploratory Investigation into Code License Infringements in Large Language Model Training DatasetsProceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering10.1145/3650105.3652298(74-85)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3650105.3652298
Duan MLi QHe BChua TNgo CKa-Wei Lee RKumar RLauw H(2024)ModelGo: A Practical Tool for Machine Learning License AnalysisProceedings of the ACM Web Conference 202410.1145/3589334.3645520(1158-1169)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645520
Liu ZLiu XZhang YZhang ZLi SNiu WZhou QZhou RZhou X(2024)LiScopeLens: An Open-Source License Incompatibility Analysis Tool Based on Scope Representation of License Terms2024 IEEE 35th International Symposium on Software Reliability Engineering (ISSRE)10.1109/ISSRE62328.2024.00013(13-24)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSRE62328.2024.00013
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Index Terms

A sentence-matching method for automatic license identification of source code files
1. Social and professional topics
  1. Computing / technology policy
    1. Intellectual property
      1. Licensing

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Information & Contributors

Information

Published In

cover image ACM Conferences

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

September 2010

534 pages

ISBN:9781450301169

DOI:10.1145/1858996

General Chair:
Charles Pecheur
Université catholique de Louvain, Belgium
,
Program Chairs:
Jamie Andrews
University of Western Ontario, Canada
,
Elisabetta Di Nitto
Politecnico di Milano, Italy

Copyright © 2010 ACM.

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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New York, NY, United States

Publication History

Published: 20 September 2010

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ASE10

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ASE10: IEEE/ACM International Conference on Automated Software Engineering

September 20 - 24, 2010

Antwerp, Belgium

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Overall Acceptance Rate 82 of 337 submissions, 24%

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Cited By

Katzy JPopescu RVan Deursen AIzadi MLo DPenta MXia XHu X(2024)An Exploratory Investigation into Code License Infringements in Large Language Model Training DatasetsProceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering10.1145/3650105.3652298(74-85)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3650105.3652298
Duan MLi QHe BChua TNgo CKa-Wei Lee RKumar RLauw H(2024)ModelGo: A Practical Tool for Machine Learning License AnalysisProceedings of the ACM Web Conference 202410.1145/3589334.3645520(1158-1169)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645520
Liu ZLiu XZhang YZhang ZLi SNiu WZhou QZhou RZhou X(2024)LiScopeLens: An Open-Source License Incompatibility Analysis Tool Based on Scope Representation of License Terms2024 IEEE 35th International Symposium on Software Reliability Engineering (ISSRE)10.1109/ISSRE62328.2024.00013(13-24)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSRE62328.2024.00013
Higashi YOhira MManabe Y(2023)Automating License Rule Generation to Help Maintain Rule-based OSS License Identification ToolsJournal of Information Processing10.2197/ipsjjip.31.231(2-12)Online publication date: 2023
https://doi.org/10.2197/ipsjjip.31.2
Win HWang HTan SChandra SBlincoe KTonella P(2023)Towards Automated Detection of Unethical Behavior in Open-Source Software ProjectsProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616314(644-656)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3616314
Xu SGao YFan LLi LCai XLiu ZJust RFraser G(2023)LiResolver: License Incompatibility Resolution for Open Source SoftwareProceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3597926.3598085(652-663)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3597926.3598085
Xu SGao YFan LLiu ZLiu YJi H(2023)LiDetector: License Incompatibility Detection for Open Source SoftwareACM Transactions on Software Engineering and Methodology10.1145/351899432:1(1-28)Online publication date: 13-Feb-2023
https://dl.acm.org/doi/10.1145/3518994
Cui XWu JWu YWang XLuo TQu SLing XYang MLiu AMuccini H(2023)An Empirical Study of License Conflict in Free and Open Source SoftwareProceedings of the 45th International Conference on Software Engineering: Software Engineering in Practice10.1109/ICSE-SEIP58684.2023.00050(495-505)Online publication date: 17-May-2023
https://dl.acm.org/doi/10.1109/ICSE-SEIP58684.2023.00050
Zhao JRen YLi BZhao XZhang J(2023)FOSSLT: An Efficient Model for Automatic Finding Open Source Software License Texts2023 2nd International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE)10.1109/CBASE60015.2023.10439089(269-275)Online publication date: 3-Nov-2023
https://doi.org/10.1109/CBASE60015.2023.10439089
Xu WHe HGao KZhou MBissyandé TKlein JBird CSarro F(2023)Understanding and Remediating Open-Source License Incompatibilities in the PyPI EcosystemProceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE56229.2023.00175(178-190)Online publication date: 11-Nov-2023
https://dl.acm.org/doi/10.1109/ASE56229.2023.00175
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