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Performance Evaluation of Impact of State Machine Transformation and Run-Time Library on a C# Application

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Hard and Soft Computing for Artificial Intelligence, Multimedia and Security (ACS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 534))

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Abstract

State machines are important behavioral models used in Model-Driven Development (MDD) of software applications. UML models are transformed into code and combined with a run-time library realizing state machine notions. Mapping of state machine concepts, including concurrent behavior issues, can be realized in various ways. We discuss several problems of call and time event processing and their impact of an application performance. In experiments, different solutions were evaluated and quantitatively compared. These variants were applied in refactoring of FXU - a framework for C# code generation and application development based on UML classes and state machine models.

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Authors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Anna Derezińska & Marian Szczykulski

Authors
  1. Anna Derezińska
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  2. Marian Szczykulski
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Corresponding author

Correspondence to Anna Derezińska .

Editor information

Editors and Affiliations

  1. Graduate School of Science and Engineeri, Ehime University Graduate School of Science and Engineeri, Ehime, Japan

    Shin-ya Kobayashi

  2. West Pomeranian University of Technology in Szczecin , Szczecin, Poland

    Andrzej Piegat

  3. West Pomeranian University of Technology in Szczecin , Szczecin, Poland

    Jerzy Pejaś

  4. West Pomeranian University of Technology in Szczecin , Szczecin, Poland

    Imed El Fray

  5. Polish Academy of Sciences, Systems Research Institute Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Derezińska, A., Szczykulski, M. (2017). Performance Evaluation of Impact of State Machine Transformation and Run-Time Library on a C# Application. In: Kobayashi, Sy., Piegat, A., Pejaś, J., El Fray, I., Kacprzyk, J. (eds) Hard and Soft Computing for Artificial Intelligence, Multimedia and Security. ACS 2016. Advances in Intelligent Systems and Computing, vol 534. Springer, Cham. https://doi.org/10.1007/978-3-319-48429-7_30

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  • DOI: https://doi.org/10.1007/978-3-319-48429-7_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48428-0

  • Online ISBN: 978-3-319-48429-7

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