• DocumentCode
    2959771
  • Title

    Performance Antipatterns as Logical Predicates

  • Author

    Cortellessa, Vittorio ; Di Marco, A. ; Trubiani, Catia

  • Author_Institution
    Dipt. di Inf., Univ. dell´´Aquila, L´´Aquila, Italy
  • fYear
    2010
  • fDate
    22-26 March 2010
  • Firstpage
    146
  • Lastpage
    156
  • Abstract
    The problem of interpreting the results of performance analysis is quite critical in the software performance domain. Mean values, variances, probability distributions are hard to interpret for providing feedback to software architects. Instead, what architects expect are solutions to performance problems, possibly in the form of architectural alternatives (e.g. split a software component in two components and re-deploy one of them). In a software performance engineering approach this path from analysis results to software alternatives still lacks of automation and is based on the skills and experience of analysts. In this paper we propose an automated approach for the performance feedback generation process based on performance antipatterns. To this aim, we model performance antipatterns as logical predicates and we provide a java engine, based on such predicates, that is able to detect performance antipatterns in an XML representation of the software system. Finally, we show the approach at work on a simple case study.
  • Keywords
    Java; XML; software architecture; software performance evaluation; Java engine; XML representation; logical predicates; performance antipatterns; performance feedback generation process; probability distributions; software architecture; software performance engineering approach; software system; Analytical models; Automation; Software performance; Software systems; Unified modeling language; XML; Antipatterns; Performance Analysis; Software Performance Engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering of Complex Computer Systems (ICECCS), 2010 15th IEEE International Conference on
  • Conference_Location
    Oxford
  • Print_ISBN
    978-1-4244-6638-2
  • Electronic_ISBN
    978-1-4244-6639-9
  • Type

    conf

  • DOI
    10.1109/ICECCS.2010.44
  • Filename
    5628619