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Comparison of type-based and alias-based component recognition for embedded systems software

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Abstract

Component-based software engineering has found broad acceptance within the embedded systems community over the last years. However, to fully exploit its potential in terms of reusability and cost-efficiency, existing code-bases have to be refactored in a component-based way. To support refactorization, static analysis techniques can be used to identify components within coarse-grained layered or even monolithic legacy software for embedded systems. We present an approach for semi-automatic extraction of components from automotive software and compare two different versions, one type-based component-recognition analysis of linear complexity with a more precise version based on a points-to analysis of almost linear algorithmic complexity. Both analyses are applied to an industrial implementation of an automotive communication stack. Each analysis is evaluated with two sets of additional manually created annotations of distinct size and precision. Thus, both analyses are fully evaluated in terms of execution-time, memory consumption and analysis precision, and its impact on the number of recognized components. We show that the analysis with higher precision allows the use of a smaller user-provided filter set and obtain a proper component recognition.

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Authors and Affiliations

  1. Compilers and Languages Group, Institute of Computer Languages, Vienna University of Technology, Vienna, Austria

    Dietmar Schreiner, Gergö Barany & Jens Knoop

  2. Institute of Computer Science, University of Applied Sciences Technikum Wien, Vienna, Austria

    Markus Schordan

Authors
  1. Dietmar Schreiner
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  2. Gergö Barany
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  3. Markus Schordan
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  4. Jens Knoop
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Correspondence to Markus Schordan.

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Schreiner, D., Barany, G., Schordan, M. et al. Comparison of type-based and alias-based component recognition for embedded systems software. Int J Softw Tools Technol Transfer 15, 41–52 (2013). https://doi.org/10.1007/s10009-012-0251-0

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  • DOI: https://doi.org/10.1007/s10009-012-0251-0

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