Automatic Quality Assessment of Source Code Comments: The JavadocMiner
N. Khamis, R. Witte, and J. Rilling. 15th International Conference on Applications of Natural Language to Information Systems (NLDB 2010), 6177, page 68--79. Cardiff, UK, Springer, (June 2010)
DOI: 10.1007/978-3-642-13881-2_7
Abstract
An important software engineering artefact used by developers and maintainers to assist in software comprehension and maintenance is source code documentation. It provides insights that help software engineers to effectively perform their tasks, and therefore ensuring the quality of the documentation is extremely important. Inline documentation is at the forefront of explaining a programmer's original intentions for a given implementation. Since this documentation is written in natural language, ensuring its quality needs to be performed manually. In this paper, we present an effective and automated approach for assessing the quality of inline documentation using a set of heuristics, targeting both quality of language and consistency between source code and its comments. We apply our tool to the different modules of two open source applications (ArgoUML and Eclipse), and correlate the results returned by the analysis with bug defects reported for the individual modules in order to determine connections between documentation and code quality.
%0 Conference Paper
%1 nldb2010b
%A Khamis, Ninus
%A Witte, René
%A Rilling, Juergen
%B 15th International Conference on Applications of Natural Language to Information Systems (NLDB 2010)
%C Cardiff, UK
%D 2010
%E Hopfe, Christina J.
%E Rezgui, Yacine
%E Métais, Elisabeth
%E Preece, Alun D.
%E Li, Haijiang
%I Springer
%K Javadoc JavadocMiner code comments quality source
%N 6177
%P 68--79
%R 10.1007/978-3-642-13881-2_7
%T Automatic Quality Assessment of Source Code Comments: The JavadocMiner
%U http://www.semanticsoftware.info/biblio/generating-nlp-corpus-java-source-code-ssl-javadoc-doclet
%X An important software engineering artefact used by developers and maintainers to assist in software comprehension and maintenance is source code documentation. It provides insights that help software engineers to effectively perform their tasks, and therefore ensuring the quality of the documentation is extremely important. Inline documentation is at the forefront of explaining a programmer's original intentions for a given implementation. Since this documentation is written in natural language, ensuring its quality needs to be performed manually. In this paper, we present an effective and automated approach for assessing the quality of inline documentation using a set of heuristics, targeting both quality of language and consistency between source code and its comments. We apply our tool to the different modules of two open source applications (ArgoUML and Eclipse), and correlate the results returned by the analysis with bug defects reported for the individual modules in order to determine connections between documentation and code quality.
@inproceedings{nldb2010b,
abstract = {An important software engineering artefact used by developers and maintainers to assist in software comprehension and maintenance is source code documentation. It provides insights that help software engineers to effectively perform their tasks, and therefore ensuring the quality of the documentation is extremely important. Inline documentation is at the forefront of explaining a programmer's original intentions for a given implementation. Since this documentation is written in natural language, ensuring its quality needs to be performed manually. In this paper, we present an effective and automated approach for assessing the quality of inline documentation using a set of heuristics, targeting both quality of language and consistency between source code and its comments. We apply our tool to the different modules of two open source applications (ArgoUML and Eclipse), and correlate the results returned by the analysis with bug defects reported for the individual modules in order to determine connections between documentation and code quality.},
added-at = {2010-07-22T15:49:22.000+0200},
address = {Cardiff, UK},
author = {Khamis, Ninus and Witte, Ren\'{e} and Rilling, Juergen},
biburl = {https://www.bibsonomy.org/bibtex/277ef8cce9a8bc1a2792e4640c43b7ef8/renew},
booktitle = {15th International Conference on Applications of Natural Language to Information Systems (NLDB 2010)},
doi = {10.1007/978-3-642-13881-2_7},
editor = {Hopfe, Christina J. and Rezgui, Yacine and M\'{e}tais, Elisabeth and Preece, Alun D. and Li, Haijiang},
interhash = {f1f6e2fa878815924ff2037cc914d8e2},
intrahash = {77ef8cce9a8bc1a2792e4640c43b7ef8},
keywords = {Javadoc JavadocMiner code comments quality source},
month = {June 23--25},
number = 6177,
pages = {68--79},
publisher = {Springer},
series = {LNCS},
timestamp = {2010-07-22T15:49:23.000+0200},
title = {{Automatic Quality Assessment of Source Code Comments: The JavadocMiner}},
url = {http://www.semanticsoftware.info/biblio/generating-nlp-corpus-java-source-code-ssl-javadoc-doclet},
year = 2010
}