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Exploiting Traceability Uncertainty Between Software Architectural Models and Performance Analysis Results

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Software Architecture (ECSA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9278))

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Abstract

While software architecture performance analysis is a well-studied field, it is less understood how the analysis results (i.e., mean values, variances, and/or probability distributions) trace back to the architectural model elements (i.e., software components, interactions among components, deployment nodes). Yet, understanding this traceability is critical for understanding the analysis result in context of the architecture. The goal of this paper is to automate the traceability between software architectural models and performance analysis results by investigating the uncertainty while bridging these two domains. Our approach makes use of performance antipatterns to deduce the logical consequences between the architectural elements and analysis results and automatically build a graph of traces to identify the most critical causes of performance flaws. We developed a tool that jointly considers SOftware and PErformance concepts (SoPeTraceAnalyzer), and it automatically builds model-to-results traceability links. The benefit of the tool is illustrated by means of a case study in the e-health domain.

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Authors and Affiliations

  1. Gran Sasso Science Institute, L’Aquila, Italy

    Catia Trubiani

  2. Johannes Kepler University, Linz, Austria

    Achraf Ghabi & Alexander Egyed

Authors
  1. Catia Trubiani
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  2. Achraf Ghabi
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  3. Alexander Egyed
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Corresponding author

Correspondence to Catia Trubiani .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Linnaeus University, Växjö, Sweden

    Danny Weyns

  2. Dipartimento di Elettronica, Informazione e Biongegneria, Politecnico di Milano, Milano, Italy

    Raffaela Mirandola

  3. Computer Science and Engineering Department, Chalmers University of Technology, Gothenburg, Sweden

    Ivica Crnkovic

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Trubiani, C., Ghabi, A., Egyed, A. (2015). Exploiting Traceability Uncertainty Between Software Architectural Models and Performance Analysis Results. In: Weyns, D., Mirandola, R., Crnkovic, I. (eds) Software Architecture. ECSA 2015. Lecture Notes in Computer Science(), vol 9278. Springer, Cham. https://doi.org/10.1007/978-3-319-23727-5_26

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  • DOI: https://doi.org/10.1007/978-3-319-23727-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23726-8

  • Online ISBN: 978-3-319-23727-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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