- Title
- Querying sequential software engineering data
- Creator
- Sun, Chengnian; Zhang, Haidong; Lou, Jian-Guang; Zhang, Hongyu; Wang, Qiang; Zhang, Dongmei; Khoo, Siau-Cheng
- Relation
- 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2014). Shing-Chi Cheung, Alessandro Orso, and Margaret-Anne Storey November 16–21, 2014 Hong Kong, China 22nd ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2014) Proceedings (Hong Kong 16-21 November, 2014) p. 700-710
- Publisher Link
- http://dx.doi.org/10.1145/2635868.2635902
- Publisher
- Association for Computing Machinery (ACM)
- Resource Type
- conference paper
- Date
- 2014
- Description
- 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.
- Subject
- sequential data; pattern matching; query; mining software repository
- Identifier
- http://hdl.handle.net/1959.13/1356814
- Identifier
- uon:31793
- Identifier
- ISBN:9781450330565
- Language
- eng
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