• DocumentCode
    971317
  • Title

    Model-based performance prediction in software development: a survey

  • Author

    Balsamo, Simonetta ; Marco, Antinisca Di ; Inverardi, Paola ; Simeoni, Marta

  • Author_Institution
    Dipt. di Informatica, Universita di Venezia, Italy
  • Volume
    30
  • Issue
    5
  • fYear
    2004
  • fDate
    5/1/2004 12:00:00 AM
  • Firstpage
    295
  • Lastpage
    310
  • Abstract
    Over the last decade, a lot of research has been directed toward integrating performance analysis into the software development process. Traditional software development methods focus on software correctness, introducing performance issues later in the development process. This approach does not take into account the fact that performance problems may require considerable changes in design, for example, at the software architecture level, or even worse at the requirement analysis level. Several approaches were proposed in order to address early software performance analysis. Although some of them have been successfully applied, we are still far from seeing performance analysis integrated into ordinary software development. In this paper, we present a comprehensive review of recent research in the field of model-based performance prediction at software development time in order to assess the maturity of the field and point out promising research directions.
  • Keywords
    formal verification; software performance evaluation; software process improvement; model-based performance prediction; requirement analysis level; software architecture level; software development process; software performance analysis; software verification; Automation; Availability; Performance analysis; Predictive models; Programming; Runtime; Software architecture; Software performance; Software systems; System software; 65; Software verification; integrated environments.; performance modeling and prediction;
  • fLanguage
    English
  • Journal_Title
    Software Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-5589
  • Type

    jour

  • DOI
    10.1109/TSE.2004.9
  • Filename
    1291833