• DocumentCode
    731518
  • 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
  • fYear
    2015
  • fDate
    16-17 May 2015
  • Firstpage
    410
  • Lastpage
    413
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mining Software Repositories (MSR), 2015 IEEE/ACM 12th Working Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/MSR.2015.51
  • Filename
    7180105