• DocumentCode
    731527
  • Title

    Employing Source Code Information to Improve Question-Answering in Stack Overflow

  • Author

    Diamantopoulos, Themistoklis ; Symeonidis, Andreas L.

  • Author_Institution
    Electr. & Comput. Eng. Dept., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
  • fYear
    2015
  • fDate
    16-17 May 2015
  • Firstpage
    454
  • Lastpage
    457
  • Abstract
    Nowadays, software development has been greatly influenced by question-answering communities, such as Stack Overflow. A new problem-solving paradigm has emerged, as developers post problems they encounter that are then answered by the community. In this paper, we propose a methodology that allows searching for solutions in Stack Overflow, using the main elements of a question post, including not only its title, tags, and body, but also its source code snippets. We describe a similarity scheme for these elements and demonstrate how structural information can be extracted from source code snippets and compared to further improve the retrieval of questions. The results of our evaluation indicate that our methodology is effective on recommending similar question posts allowing community members to search without fully forming a question.
  • Keywords
    question answering (information retrieval); software engineering; source code (software); question-answering; similarity scheme; software development; source code information; source code snippets; stack overflow; structural information; Communities; Data mining; HTML; Indexes; Java; Search problems; Software; Indexing; Search Engines; Source Code Mining;
  • 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.2015.62
  • Filename
    7180116