• DocumentCode
    637296
  • Title

    Performance evaluation of VSM and LSI models to determine bug reports similarity

  • Author

    Chawla, Indu ; Singh, S.K.

  • Author_Institution
    Dept. of Comput. Sci., Jaypee Inst. of Inf. Technol., Noida, India
  • fYear
    2013
  • fDate
    8-10 Aug. 2013
  • Firstpage
    375
  • Lastpage
    380
  • Abstract
    Bug reports of open source software systems are increasing exponentially. One reason for growing bug reports is that bug reporters do not browse the bug repository before submitting a bug report. There may be some similar bugs already reported: one, which are exactly similar or duplicate and other, which are semantically similar means they may belong to the same software component or files. The information contained in the previously reported similar bugs can be helpful in fixing and resolving the newly reported bugs. In this paper, we applied and compared performance of two information retrieval (IR) models: Vector Space Model (VSM) and Latent Semantic Indexing (LSI), in extracting existing similar bug reports. The performance of these two models have been evaluated based on the Top Ten results retrieved by them for relevant bug reports. Experiments have been conducted on 106 bug reports of three components from Google chrome, browser. Result shows that LSI performs better in most cases in comparison to VSM.
  • Keywords
    information retrieval; pattern matching; performance evaluation; program debugging; public domain software; software management; Google chrome; IR model; LSI models; VSM; browser; bug reports similarity determination; bug repository; information retrieval; latent semantic indexing; open source software systems; performance evaluation; vector space model; Computer bugs; Indexing; Information retrieval; Large scale integration; Semantics; Software; Vectors; Bug report; Latent Semantic Indexing; Vector space model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Contemporary Computing (IC3), 2013 Sixth International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-0190-6
  • Type

    conf

  • DOI
    10.1109/IC3.2013.6612223
  • Filename
    6612223