Authors: Chengnian Sun Haidong Zhang Jian-Guang Lou Hongyu Zhang Qiang Wang Dongmei Zhang Siau-Cheng Khoo
Venue: FSE ACM SIGSOFT International Symposium on Foundations of Software Engineering, pp. 700-710, 2014
Year: 2014
Abstract: We propose a pattern-based approach to effectively and efficiently analyzing sequential software engineering (SE) data. Different from other types of SE data, sequential SE data preserves unique temporal properties, which cannot be easily analyzed without much programming effort. In order to facilitate the analysis of sequential SE data, we design a sequential pattern query language (SPQL), which specifies the temporal properties based on regular expressions, and is enhanced with variables and statements to store and manipulate matching states. We also propose a query engine to effectively process the SPQL queries. We have applied our approach to analyze two types of SE data, namely bug report history and source code change history. We experiment with 181,213 Eclipse bug reports and 323,989 code revisions of Android. SPQL enables us to explore interesting temporal properties underneath these sequential data with a few lines of query code and low matching overhead. The analysis results can help better under- stand a software process and identify process violations.
BibTeX:
@inproceedings{chengniansun2014qssed,
author = "Chengnian Sun and Haidong Zhang and Jian-Guang Lou and Hongyu Zhang and Qiang Wang and Dongmei Zhang and Siau-Cheng Khoo",
title = "Querying Sequential Software Engineering Data",
year = "2014",
pages = "700-710",
booktitle = "Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering
"
}
Plain Text:
Chengnian Sun, Haidong Zhang, Jian-Guang Lou, Hongyu Zhang, Qiang Wang, Dongmei Zhang, and Siau-Cheng Khoo, "Querying Sequential Software Engineering Data," ACM SIGSOFT International Symposium on Foundations of Software Engineering, pp. 700-710