Build System Analysis with Link Prediction
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.
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
SAC '14: Proceedings of the 29th ACM Symposium on Applied Computing: March 24 - 28, 2014, Gyeongju, Korea
First Page
1184
Last Page
1186
ISBN
9781450324694
Identifier
10.1145/2554850.2555134
Publisher
ACM
City or Country
New York
Citation
XIA, Xin; LO, David; WANG, Xinyu; and ZHOU, Bo.
Build System Analysis with Link Prediction. (2014). SAC '14: Proceedings of the 29th ACM Symposium on Applied Computing: March 24 - 28, 2014, Gyeongju, Korea. 1184-1186.
Available at: https://ink.library.smu.edu.sg/sis_research/2035
Additional URL
http://dx.doi.org/10.1145/2554850.2555134