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Instrumentation-Driven Validation of Dataflow Applications

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Abstract

Dataflow modeling offers a myriad of tools for designing and optimizing signal processing systems. A designer is able to take advantage of dataflow properties to effectively tune the system in connection with functionality and different performance metrics. However, a disparity in the specification of dataflow properties and the final implementation can lead to incorrect behavior that is difficult to detect. This motivates the problem of ensuring consistency between dataflow properties that are declared or otherwise assumed as part of dataflow-based application models, and the dataflow behavior that is exhibited by implementations that are derived from the models. In this paper, we address this problem by introducing a novel dataflow validation framework (DVF) that is able to identify disparities between an application’s formal dataflow representation and its implementation. DVF works by instrumenting the implementation of an application and monitoring the instrumentation data as the application executes. This monitoring process is streamlined so that DVF achieves validation without major overhead. We demonstrate the utility of our DVF through design and implementation case studies involving an automatic speech recognition application, a JPEG encoder, and an acoustic tracking application.

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Authors and Affiliations

  1. Department of Electrical, Computer Engineering, University of Maryland, College Park, MD, USA

    Ilya Chukhman, Yang Jiao & Shuvra S. Bhattacharyya

  2. Electronics, Electrical, Computer Engineering, Technische Universitat Munchen, Munich, Germany

    Haifa Ben Salem

  3. Institute for Advanced Computer Studies, University of Maryland, College Park, MD, 20742, USA

    Shuvra S. Bhattacharyya

  4. Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland

    Shuvra S. Bhattacharyya

Authors
  1. Ilya Chukhman
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  2. Yang Jiao
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  3. Haifa Ben Salem
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  4. Shuvra S. Bhattacharyya
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Correspondence to Ilya Chukhman.

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Chukhman, I., Jiao, Y., Salem, H.B. et al. Instrumentation-Driven Validation of Dataflow Applications. J Sign Process Syst 84, 383–397 (2016). https://doi.org/10.1007/s11265-015-1073-6

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  • DOI: https://doi.org/10.1007/s11265-015-1073-6

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