Sentence-to-Code Traceability Recovery with Domain Ontologies
S. Hayashi, T. Yoshikawa, and M. Saeki. Software Engineering Conference (APSEC), 2010 17th Asia Pacific, page 385 -394. (30 2010-dec. 3 2010)
Abstract
We propose an ontology-based technique for recovering trace ability links between a natural language sentence specifying features of a software product and the source code of the product. Some software products have been released without detailed documentation. To automatically detect code fragments associated with sentences describing a feature, the relations between source code structures and problem domains are important. We model the knowledge of the problem domains as domain ontologies having concepts of the domains and their relations. Using semantic relations on the ontologies in addition to method invocation relations and the similarity between an identifier on the code and words in the sentences, we locate the code fragments corresponding to the given sentences. Additionally, our prioritization mechanism which orders the located results of code fragments based on the ontologies enables users to select and analyze the results effectively. To show effectiveness of our approach in terms of accuracy, a case study was carried out with our proof-of-concept tool and summarized.
%0 Conference Paper
%1 Hayashi2010
%A Hayashi, S.
%A Yoshikawa, T.
%A Saeki, M.
%B Software Engineering Conference (APSEC), 2010 17th Asia Pacific
%D 2010
%K source_code ontology
%P 385 -394
%T Sentence-to-Code Traceability Recovery with Domain Ontologies
%X We propose an ontology-based technique for recovering trace ability links between a natural language sentence specifying features of a software product and the source code of the product. Some software products have been released without detailed documentation. To automatically detect code fragments associated with sentences describing a feature, the relations between source code structures and problem domains are important. We model the knowledge of the problem domains as domain ontologies having concepts of the domains and their relations. Using semantic relations on the ontologies in addition to method invocation relations and the similarity between an identifier on the code and words in the sentences, we locate the code fragments corresponding to the given sentences. Additionally, our prioritization mechanism which orders the located results of code fragments based on the ontologies enables users to select and analyze the results effectively. To show effectiveness of our approach in terms of accuracy, a case study was carried out with our proof-of-concept tool and summarized.
@inproceedings{Hayashi2010,
abstract = {We propose an ontology-based technique for recovering trace ability links between a natural language sentence specifying features of a software product and the source code of the product. Some software products have been released without detailed documentation. To automatically detect code fragments associated with sentences describing a feature, the relations between source code structures and problem domains are important. We model the knowledge of the problem domains as domain ontologies having concepts of the domains and their relations. Using semantic relations on the ontologies in addition to method invocation relations and the similarity between an identifier on the code and words in the sentences, we locate the code fragments corresponding to the given sentences. Additionally, our prioritization mechanism which orders the located results of code fragments based on the ontologies enables users to select and analyze the results effectively. To show effectiveness of our approach in terms of accuracy, a case study was carried out with our proof-of-concept tool and summarized.},
added-at = {2011-10-11T22:25:02.000+0200},
author = {Hayashi, S. and Yoshikawa, T. and Saeki, M.},
biburl = {https://www.bibsonomy.org/bibtex/23c6203d657e46a16a8b90ab8f0180df4/sjbutler},
booktitle = {Software Engineering Conference (APSEC), 2010 17th Asia Pacific},
interhash = {6f5899084b5964ace957ef53bff84a77},
intrahash = {3c6203d657e46a16a8b90ab8f0180df4},
keywords = {source_code ontology},
month = {30 2010-dec. 3},
pages = {385 -394},
timestamp = {2011-10-11T22:25:02.000+0200},
title = {Sentence-to-Code Traceability Recovery with Domain Ontologies},
year = 2010
}