Title :
Semi-automatically extracting FAQs to improve accessibility of software development knowledge
Author :
Hens, S. ; Monperrus, Martin ; Mezini, Mira
Author_Institution :
Tech. Univ. Darmstadt, Darmstadt, Germany
Abstract :
Frequently asked questions (FAQs) are a popular way to document software development knowledge. As creating such documents is expensive, this paper presents an approach for automatically extracting FAQs from sources of software development discussion, such as mailing lists and Internet forums, by combining techniques of text mining and natural language processing. We apply the approach to popular mailing lists and carry out a survey among software developers to show that it is able to extract high-quality FAQs that may be further improved by experts.
Keywords :
data mining; document handling; natural language processing; software engineering; text analysis; FAQ semiautomatic extraction; frequently asked questions; mailing lists; natural language processing; software development knowledge accessibility; software development knowledge documentation; text mining; Data mining; Data models; Documentation; Java; Noise; Programming; Software;
Conference_Titel :
Software Engineering (ICSE), 2012 34th International Conference on
Conference_Location :
Zurich
Print_ISBN :
978-1-4673-1066-6
Electronic_ISBN :
0270-5257
DOI :
10.1109/ICSE.2012.6227139