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Tulsa: A Tool for Transforming UML to Layered Queueing Networks for Performance Analysis of Data Intensive Applications

  • Chen Li
  • Taghreed Altamimi
  • Mana Hassanzadeh Zargari
  • Giuliano Casale
  • Dorina Petriu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10503)

Abstract

Motivated by the problem of detecting software performance anti-patterns in data-intensive applications (DIAs), we present a tool, Tulsa, for transforming software architecture models specified through UML into Layered Queueing Networks (LQNs), which are analytical performance models used to capture contention across multiple software layers. In particular, we generalize an existing transformation based on the Epsilon framework to generate LQNs from UML models annotated with the DICE profile, which extends UML to modelling DIAs based on technologies such as Apache Storm.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Chen Li
    • 1
  • Taghreed Altamimi
    • 2
  • Mana Hassanzadeh Zargari
    • 2
  • Giuliano Casale
    • 1
  • Dorina Petriu
    • 2
  1. 1.Imperial College LondonLondonUK
  2. 2.Carleton UniversityOttawaCanada

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