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![Context: JSON and JSON Schema
• JSON is an open, textual, human readable data
serialization format (.json) with a wide range of application,
primarily used in data exchange Web scenarios
[1] IETF, “JSON Schema Draft 2020-12,” https://json-schema.org/draft/ 2020-12/json-schema-core.html, accessed: 2021-19-02.
[2] JSON Schema meta-schema: https://json-schema.org/draft-07/schema
{
"name": "Alessandro",
"surname": "Colantoni",
"affiliation": {
"universityName": "Johannes Kepler University",
"city": "Linz"
},
"contacts": [
{"email": "alessandro.colantoni@jku.at"},
{"phone": "+4373224684248"},
]
} .json
“name” : “value” pairs
[array]
{object}
JSON document / schema instance
JSON document / schema
• JSON Schema is a draft standard issued by IETF.
A schema is “a JSON media type for defining the structure
of JSON data. JSON Schema is intended to define
validation, documentation, hyperlink navigation, and
interaction control of JSON data.” [1]
{
"$schema": "http://json-schema.org/draft-07/schema#"
"type":"object",
"properties":{
"name":{"type":"string},
"surname":{"type":"string}
},
"additionalProperties":true
} .json
Reference to JSON Schema draft standard
contacts array property not foreseen but is allowed!
• IETF publishes a JSON Schema Draft [2] every 6 months
{
"$schema": "http://json-schema.org/draft-07/schema#",
"$id": "http://json-schema.org/draft-07/schema#",
"title": "Core schema meta-schema",
…
} .json
JSON document / (meta)schema instance
JSON document / (meta)schema
Defined by itself
3](https://image.slidesharecdn.com/models-presentation-extended-211105141808/75/Leveraging-Model-Driven-Technologies-for-JSON-Artefacts-The-Shipyard-Case-Study-3-2048.jpg)
![Context: JSON and JSON Schema
• Additional Properties: true
In this case any JSON fragment can be attached to a
schema instance.
We created the JSONDocumentFragment for this purpose,
to support validation of such JSON fragments within our
Xtext-based editors.
{
"name": "Alessandro",
"surname": "Colantoni“,
"affiliation": {
"universityName": "Johannes Kepler University",
"city": "Linz"
},
"contacts": [
{"email": "alessandro.colantoni@jku.at"},
{"phone": "+4373224684248"},
]
} .json
“name” : “value” pairs
[array]
{object}
JSON document / schema instance
JSON document / schema
{
"$schema": "http://json-schema.org/draft-07/schema#"
"type":"object",
"properties":{
"name":{"type":"string},
"surname":{"type":"string}
},
"additionalProperties":true
} .json
Reference to JSON Schema draft standard
contacts array property not foreseen but is allowed!
{
"$schema": "http://json-schema.org/draft-07/schema#",
"$id": "http://json-schema.org/draft-07/schema#",
"title": "Core schema meta-schema",
…
} .json
JSON document / (meta)schema instance
JSON document / (meta)schema
Defined by itself
20](https://image.slidesharecdn.com/models-presentation-extended-211105141808/75/Leveraging-Model-Driven-Technologies-for-JSON-Artefacts-The-Shipyard-Case-Study-20-2048.jpg)
Uploaded byLuca Berardinelli
Leveraging Model-Driven Technologies for JSON Artefacts: The Shipyard Case Study
The document discusses the application of model-driven technologies to JSON and JSON schema through a case study involving Shipyard, focusing on continuous delivery workflows in DevOps. It outlines a bridging approach to enhance modeling, validation, and consistency management of JSON artifacts while integrating modelware with JSONware. Future work includes gathering feedback from the Keptn community to evaluate the adoption of model-driven engineering in an MDE-agnostic setting.
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Leveraging Model-Driven Technologies for JSON Artefacts: The Shipyard Case Study
- 1. Leveraging Model-Driven Technologies forJSON Artefacts: The Shipyard Case Study Alessandro Colantoni, Antonio Garmendia, Luca Berardinelli, Manuel Wimmer Institute for Business Informatics – Software Engineering Johannes Kepler University, Linz, Austria Johannes Bräuer Dynatrace GmbH, Linz MODELS 2021, Practice and Innovation Track, Oct 14th, 2021 (virtual)
- 2. Outline ◦Context: ▪ JSON &JSON Schema ▪ Use Case Scenarios ◦MDE for JSON/JSON Schema: ▪ Bridging Approach steps in details ▪ Case study in DevOps domain: Keptn and Shipyard DSL ◦Conclusions and Future Work 2
- 3. Context: JSON andJSON Schema • JSON is an open, textual, human readable data serialization format (.json) with a wide range of application, primarily used in data exchange Web scenarios [1] IETF, “JSON Schema Draft 2020-12,” https://json-schema.org/draft/ 2020-12/json-schema-core.html, accessed: 2021-19-02. [2] JSON Schema meta-schema: https://json-schema.org/draft-07/schema { "name": "Alessandro", "surname": "Colantoni", "affiliation": { "universityName": "Johannes Kepler University", "city": "Linz" }, "contacts": [ {"email": "alessandro.colantoni@jku.at"}, {"phone": "+4373224684248"}, ] } .json “name” : “value” pairs [array] {object} JSON document / schema instance JSON document / schema • JSON Schema is a draft standard issued by IETF. A schema is “a JSON media type for defining the structure of JSON data. JSON Schema is intended to define validation, documentation, hyperlink navigation, and interaction control of JSON data.” [1] { "$schema": "http://json-schema.org/draft-07/schema#" "type":"object", "properties":{ "name":{"type":"string}, "surname":{"type":"string} }, "additionalProperties":true } .json Reference to JSON Schema draft standard contacts array property not foreseen but is allowed! • IETF publishes a JSON Schema Draft [2] every 6 months { "$schema": "http://json-schema.org/draft-07/schema#", "$id": "http://json-schema.org/draft-07/schema#", "title": "Core schema meta-schema", … } .json JSON document / (meta)schema instance JSON document / (meta)schema Defined by itself 3
- 4. Context: Actors andUse Cases Metaschema Specification Tool Support Domain-specific Activities (schemas and schema instances) Tool Provider(s) Domain Expert(s) Data/Language Engineer(s) Schema Specification Managing (meta)schemas and schema instances. Typical tools include editors, parsers, validators, “utilities”… Data Engineers define data structures. JSON Schema is used also for defining the structure of “scripting languages”. JSON users needing JSON for their domain. This is the largest category. IETF is issuing and maintaining metaschema drafts, i.e., IETF. https://json-schema.org/implementations.html JSON users schema instance c2 metaschema c2 schema Now… Meta-Language Engineer 4
- 5. Contributions: Bridging JSONware/Modelware(1) Metaschema Specification Tool Support Domain-specific Activities (schemas and schema instances) Tool Provider(s) Domain Expert(s) Data/Language Engineer(s) Schema Specification JSON users schema instance c2 metaschema c2 schema JSONware TS M3 M2 M1 1 Modelware TS model c2 metalanguage c2 metamodel M3 M2 M1 1 Semi-automated JSONware/Modelware Bridging Approach. Metalayers are explicitly spotted in JSONware. Meta-Language Engineer …After 5
- 6. Contributions: Modeling andValidation Support (2) Metaschema Specification Tool Support Domain-specific Activities (schemas and schema instances) Tool Provider(s) Domain Expert(s) Data/Language Engineer(s) Schema Specification JSON users schema instance c2 metaschema c2 schema JSONware TS M3 M2 M1 1 Modelware TS model c2 metalanguage c2 metamodel M3 M2 M1 Enabling Modelware-native Tool Support in addition to JSONware one, thanks to tool support generarion capabilities of language workbenches. (Meta)Language Engineers become potential Tool Providers Modelware-native Support «extend» Validation Support Modeling Support «extend» «extend» «include» «include» Consistency Checking Support «include» 2 2 …After Meta-Language Engineer Colantoni, B. Horvath, A. Horvath, L. Berardinelli, and M. Wimmer, “Towards Continuous Consistency Checking of DevOps Artefacts,” in Proceedings of the 24rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2021, p. 6. 6 @DevOps 2021 (Monday)
- 7. Contributions: Transparent toJSON users (3) Metaschema Specification Tool Support Domain-specific Activities (schemas and schema instances) Tool Provider(s) Domain Expert(s) Data/Language Engineer(s) Schema Specification JSON users schema instance c2 metaschema c2 schema MDE users JSONware TS M3 M2 M1 1 Modelware TS model c2 metalanguage c2 metamodel M3 M2 M1 «include» Transparent Approach for JSON users, typically MDE-agnostic, by adopting JSON textual concrete syntax 3 …After Meta-Language Engineer JSONware-native support 3 Modelware-native Support «extend» Validation Support Modeling Support «extend» «extend» «include» «include» Consistency Checking Support «include» 2 7 Colantoni, B. Horvath, A. Horvath, L. Berardinelli, and M. Wimmer, “Towards Continuous Consistency Checking of DevOps Artefacts,” in Proceedings of the 24rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2021, p. 6. @DevOps 2021 (Monday)
- 8. Case Study Scenario:Shipyard DSL for Keptn (CD) Metaschema Specification Tool Support Continuous Delivery Workflow Specification (DevOps) Tool Provider(s) Domain Expert(s) Meta-Language Engineer Data/Language Engineer(s) Schema Specification JSON users schema instance c2 metaschema c2 schema MDE users JSONware TS M3 M2 M1 1 Modelware TS model c2 metalanguage c2 metamodel M3 M2 M1 is an open-source project for orchestrating continuous delivery (CD) and operational processes of cloud-native applications https://keptn.sh/ JSONware-native support 3 Modelware-native Support «extend» Validation Support Modeling Support «extend» «extend» «include» «include» Consistency Checking Support «include» 2 «include» 8 Colantoni, B. Horvath, A. Horvath, L. Berardinelli, and M. Wimmer, “Towards Continuous Consistency Checking of DevOps Artefacts,” in Proceedings of the 24rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2021, p. 6. @DevOps 2021 (Monday)
- 9. Bridging JSONware/Modelware inDetails • 8 steps across meta layers (domain independent/specific) • Different stakeholders / different views • Metalanguage Engineers (i.e., IETF) perform manual steps • Other stakeholders enjoy automation via novel transformations (JsonSchema2Ecore) and existing ones (e.g., Ecore2Xtext) • Supporting Technologies: EMF, Xtext, ATL, Xtend : 7-8 Domain Expert(s) Tool Provider(s) Language Engineer(s) : 2,6 : 3-6 Meta-Language Engineer : 1-2 metaschema JSONware c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 schema schema model c2 4 3 schema metamodel schema grammar 5 6 document (schema instance) document model 7 8 domain-specific domain-independent 9 Let’s introduce it step by step
- 10. Approach: Generate MetaschemaArtefacts c2 metaschema JSONware TS c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 Meta-Language Engineer : 1-2 domain-independent 10 • Step 1: Metaschema Metamodel and metaschema-based OCL specification • Step 2: Xtext grammar generation and manual refactoring
- 11. Approach: Generate MetaschemaArtefacts document (schema instance) c2 metaschema c2 schema JSONware c2 Ecore metalanguage metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 Meta-Language Engineer : 1-2 domain-independent metaschema metamodel 11 + OCL M1 + OCL • Step 1: Metaschema Metamodel and metaschema-based OCL specification • Step 2: Xtext grammar generation and manual refactoring
- 12. Approach: Generate MetaschemaArtefacts metaschema JSONware c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 c2 + OCL • Step 1: Metaschema Metamodel and metaschema-based OCL specification • Step 2: Xtext grammar generation and manual refactoring Meta-Language Engineer : 1-2 domain-independent 12 + OCL
- 13. Approach: Editing/Modeling SchemaDocuments metaschema JSONware c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 5 6 7 8 3 c2 c2 • Step 3: Schema Model in Modelware • Step 4: JSONware/Modelware bidirectional bridge Data/Language Engineer(s) : 3-6 Shipyard Schema: CD stages as sequences of stages and then tasks domain-specific schema domain-independent 13 + OCL 3 schema model 4 4
- 14. domain-specific Approach: Generate SchemaArtefacts metaschema JSONware c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 c2 4 3 schema grammar 6 • Step 5: Generate Schema Metamodel • Step 6: Generate Schema Grammar and Shipyard Schema metamodel automatically generated via JSONSchema to Ecore schema model domain-independent Data/Language Engineer(s) : 3-6 schema metamodel Modeling Metaschema-based Validation (arbitrary warnings possible) + OCL domain-specific OCL constraints 14 + OCL onSave (no errors) + OCL 5 schema
- 15. Approach: Modeling/Validating CDWorkflow in Shipyard metaschema JSONware c2 Ecore metalanguage c2 metaschema metamodel Modelware (via EMF) c2 Xtext metagrammar c2 metaschema grammar 1 2 M3 M2 M1 • Step 7: Modeling your own JSON document as JSON schema instance • Step 8: By construction compatibility with JSONware (you are indeed editing in JSON document (schema instance) c2 schema c2 schema schema metamodel schema grammar document model schema model c2 c2 4 5 6 7 8 3 c2 schema schema model c2 4 3 schema metamodel schema grammar 5 6 Continuous Delivery Workflow in Shipyard 7 8 domain-specific domain-independent : 7-8 Domain Expert(s) 15 Modeling and Validation + OCL + OCL + OCL document model document (schema instance)
- 16. Practical Impact forDevOps Experts using Keptn. RQ1: Is our approach capable of presenting the different versions of the Shipyard language initially defined with JSON Schema? Yes, we applied the approach for 4 Shipyard DSL versions so far. RQ2: As the Shipyard language is subject to evolution, can we support the co-evolution of existing DevOps workflows? Yes, we pave the way to co-evolution support classifying changes in conformance breaking/non-breaking changes. 16
- 17. Conclusions and FutureWork • We presented a bridge between JSONware and Modelware (via Eclipse-based technologies) • Goal: bringing the benefits of model-driven technologies to JSONware • We concentrated on Modeling and Validation. Consistency Management across JSON artefacts have been presented at DevOps workshop • We are going to collect and analyse feedback from Keptn community to assess the introduction of MDE to an MDE-agnostic community 17
- 18. Leveraging Model-Driven Technologies forJSON Artefacts: The Shipyard Case Study Alessandro Colantoni, Antonio Garmendia, Luca Berardinelli, Manuel Wimmer Institute for Business Informatics – Software Engineering Johannes Kepler University, Linz, Austria Johannes Bräuer Dynatrace GmbH, Linz MODELS 2021, Practice and Innovation Track, Oct 14th, 2021 (virtual) Thanks for your attention Question Time
- 19. On JSONSchema2Ecore Transformation Isbidirectional? MDE Expert viewpoint: No. • We provide a JSON Schema to Ecore transformation • We do not provide (yet) an Ecore to JSON Schema. An arbitrary Ecore cannot be transformed into JSON Schema JSON Schema Expert (MDE agnostic) viewpoint: n.a. • She/he is an unaware modeler thanks JSON Native concrete syntax preserved. 19
- 20. Context: JSON andJSON Schema • Additional Properties: true In this case any JSON fragment can be attached to a schema instance. We created the JSONDocumentFragment for this purpose, to support validation of such JSON fragments within our Xtext-based editors. { "name": "Alessandro", "surname": "Colantoni“, "affiliation": { "universityName": "Johannes Kepler University", "city": "Linz" }, "contacts": [ {"email": "alessandro.colantoni@jku.at"}, {"phone": "+4373224684248"}, ] } .json “name” : “value” pairs [array] {object} JSON document / schema instance JSON document / schema { "$schema": "http://json-schema.org/draft-07/schema#" "type":"object", "properties":{ "name":{"type":"string}, "surname":{"type":"string} }, "additionalProperties":true } .json Reference to JSON Schema draft standard contacts array property not foreseen but is allowed! { "$schema": "http://json-schema.org/draft-07/schema#", "$id": "http://json-schema.org/draft-07/schema#", "title": "Core schema meta-schema", … } .json JSON document / (meta)schema instance JSON document / (meta)schema Defined by itself 20