• DocumentCode
    2513707
  • Title

    The prediction of software aging trend based on user intention

  • Author

    Guo, Jun ; Ju, Ying ; Wang, Yunsheng ; Li, Xianli ; Zhang, Bin

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2010
  • fDate
    28-30 Nov. 2010
  • Firstpage
    206
  • Lastpage
    209
  • Abstract
    Owing to the limitation of traditional software aging trend prediction method that based on time and based on measurement in dealing with sudden large scale concurrent questions, this paper proposes a new software aging trend prediction method which is based on user intention. This method predicts the trend of software aging according to the quantity of user requests for each components during the moment of system operation, and the software aging damage with each component is requested once.The experiment indicates, compared with the measurement method, this method has highter accuracy in dealing with sudden large scale concurrent questions.
  • Keywords
    data mining; software fault tolerance; software aging damage; software aging trend prediction; sudden large scale concurrent questions; system operation; user intention; user requests; Aging; Association rules; Memory management; Servers; Software; Software measurement; association rule mining; cumulation damage; multivariate linear regression analysis; software aging; user intention prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Computing and Telecommunications (YC-ICT), 2010 IEEE Youth Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8883-4
  • Type

    conf

  • DOI
    10.1109/YCICT.2010.5713081
  • Filename
    5713081