Build system analysis with link prediction

Xin Xia, David Lo, Xinyu Wang, Bo Zhou

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - The 29th Annual ACM Symposium on Applied Computing, SAC 2014
Subtitle of host publicationMarch 24 – 28, 2014, Gyeongju, Korea
EditorsChih-Cheng Hung , Jiman Hong
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages1184-1186
Number of pages3
ISBN (Print)9781450324694
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventACM Symposium on Applied Computing 2014 - Gyeongju, Korea, Republic of (South)
Duration: 24 Mar 201428 Mar 2014
Conference number: 29th
http://www.sigapp.org/sac/sac2014/
https://dl.acm.org/doi/proceedings/10.1145/2554850 (Proceedings)

Conference

ConferenceACM Symposium on Applied Computing 2014
Abbreviated titleSAC 2014
CountryKorea, Republic of (South)
CityGyeongju
Period24/03/1428/03/14
Internet address

Keywords

  • Build System
  • Link Prediction
  • Makefile

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