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Pyrus: An Online Modeling Environment for No-Code Data-Analytics Service Composition

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Leveraging Applications of Formal Methods, Verification and Validation (ISoLA 2021)

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Abstract

We present Pyrus, a domain-specific online modeling environment for building graphical processes for data analysis, machine learning and artificial intelligence. Pyrus aims at bridging the gap between de facto (often Python-based) standards as established by the Jupyter platform, and the tradition to model data analysis workflows in a dataflow-driven fashion. Technically, Pyrus integrates established online IDEs like Jupyter and allows users to graphically combine available functional components to dataflow-oriented workflows in a collaborative fashion without writing a single line of code. Following a controlflow/dataflow conversion and compilation, the execution is then delegated to the underlying platforms. Both the inputs to a modeled workflow and the results of its execution can be specified and viewed without leaving Pyrus which supports a seamless cooperation between data science experts and programmers. The paper illustrates the fundamental concepts, the employed domain-specific language, and, in particular, the role of the integrated IDE’s in an example-driven fashion which can be reproduced in the available online modeling environment.

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Notes

  1. 1.

    Project: https://gitlab.com/scce/ml-process, Demo: https://ls5vs023.cs.tu-dortmund.de, (For reviewing only) Login:isola21 Password:isola21.

  2. 2.

    https://gitlab.com/scce/cinco.

  3. 3.

    https://gitlab.com/scce/pyro.

  4. 4.

    Demo: https://ls5vs026.cs.tu-dortmund.de/. (For reviewing only) Login:isola21 Password:isola21.

  5. 5.

    https://ls5vs026.cs.tu-dortmund.de/.

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Correspondence to Philip Zweihoff or Bernhard Steffen .

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Zweihoff, P., Steffen, B. (2021). Pyrus: An Online Modeling Environment for No-Code Data-Analytics Service Composition. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. ISoLA 2021. Lecture Notes in Computer Science(), vol 13036. Springer, Cham. https://doi.org/10.1007/978-3-030-89159-6_2

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