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Article
Build System Analysis with Link Prediction
SAC '14: Proceedings of the 29th ACM Symposium on Applied Computing: March 24 - 28, 2014, Gyeongju, Korea
  • Xin XIA, Zhejiang University
  • David LO, Singapore Management University
  • Xinyu WANG
  • Bo ZHOU
Publication Type
Conference Proceeding Article
Publication Date
3-2014
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.

ISBN
9781450324694
Identifier
10.1145/2554850.2555134
Publisher
ACM
City or Country
New York
Additional URL
http://dx.doi.org/10.1145/2554850.2555134
Citation Information
Xin XIA, David LO, Xinyu WANG and Bo ZHOU. "Build System Analysis with Link Prediction" SAC '14: Proceedings of the 29th ACM Symposium on Applied Computing: March 24 - 28, 2014, Gyeongju, Korea (2014) p. 1184 - 1186
Available at: http://works.bepress.com/david_lo/136/