Leveraging Model-Driven Technologies for JSON Artefacts: The Shipyard Case Study

Alessandro Colantoni, Antonio Garmendia, Luca Berardinelli, Manuel Wimmer, Johannes Bräuer

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

With JSON’s increasing adoption, the need for structural constraints and validation capabilities led to JSON Schema, a dedicated meta-language to specify languages which are in turn used to validate JSON documents. Currently, the standardisation process of JSON Schema and the implementation of adequate tool support (e.g., validators and editors) are work in progress. However, the periodic issuing of newer JSON Schema drafts makes tool development challenging. Nevertheless, many JSON Schemas as language definitions exist, but JSON documents are still mostly edited in basic text-based editors. To tackle this challenge, we investigate in this paper how Model-Driven Engineering (MDE) methods for language engineering can help in this area. Instead of reinventing the wheel of building up particular technologies directly for JSON, we study how the existing MDE infrastructures may be utilized for JSON. In particular, we present a bridge between the JSONware and Modelware technical spaces to exchange languages and documents. Based on this bridge, our approach supports language engineers, domain experts, and tool providers in editing, validating, and generating tool support with enhanced capabilities for JSON schemas and their documents. We evaluate our approach with Shipyard, a JSON Schema-based language for the workflow specification for Keptn, an open-source tool for DevOps automation of cloud-native applications. The results of the case study show that proper editors and language evolution support from MDE can be reused and, at the same time, the surface syntax of JSON is maintained.
Original languageEnglish
Title of host publicationACM / IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS), October 10-15, 2021.
Number of pages10
Publication statusPublished - Oct 2021

Fields of science

  • 202017 Embedded systems
  • 102002 Augmented reality
  • 102006 Computer supported cooperative work (CSCW)
  • 102015 Information systems
  • 102020 Medical informatics
  • 102022 Software development
  • 102034 Cyber-physical systems
  • 201132 Computational engineering
  • 201305 Traffic engineering
  • 207409 Navigation systems
  • 502032 Quality management
  • 502050 Business informatics
  • 503015 Subject didactics of technical sciences

JKU Focus areas

  • Digital Transformation

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