Title :
Quality Questions Need Quality Code: Classifying Code Fragments on Stack Overflow
Author :
Duijn, Maarten ; Kucera, Adam ; Bacchelli, Alberto
Author_Institution :
Delft Univ. of Technol., Delft, Netherlands
Abstract :
Stack Overflow (SO) is a question and answers (Q&A) web platform on software development that is gaining in popularity. With increasing popularity often comes a very unwelcome side effect: A decrease in the average quality of a post. To keep Q&A websites like SO useful it is vital that this side effect is countered. Previous research proved to be reasonably successful in using properties of questions to help identify low quality questions to be later reviewed and improved. We present an approach to improve the classification of high and low quality questions based on a novel source of information: the analysis of the code fragments in SO questions. We show that we get similar performance to classification based on a wider set of metrics thus potentially reaching a better overall classification.
Keywords :
Web sites; pattern classification; question answering (information retrieval); Q&A Websites; SO questions; code fragment classification; quality code; quality questions; stack overflow; Accuracy; Algorithm design and analysis; Classification algorithms; Correlation; Decision trees; Java; Measurement;
Conference_Titel :
Mining Software Repositories (MSR), 2015 IEEE/ACM 12th Working Conference on
Conference_Location :
Florence
DOI :
10.1109/MSR.2015.51