Relational reference attribute grammars: Improving continuous model validation
(2020) In Journal of Computer Languages 57.- Abstract
- Just like current software systems, conceptual models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated, validated and serialized. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform incremental analysis efficiently using dynamic dependency tracking. However, not all features used in conceptual modelling are directly available in RAGs. In particular, support for noncontainment model relations is only available through encodings. We present an approach called Relational RAGs to directly model uni- and bidirectional noncontainment relations in RAGs... (More)
- Just like current software systems, conceptual models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated, validated and serialized. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform incremental analysis efficiently using dynamic dependency tracking. However, not all features used in conceptual modelling are directly available in RAGs. In particular, support for noncontainment model relations is only available through encodings. We present an approach called Relational RAGs to directly model uni- and bidirectional noncontainment relations in RAGs and provide efficient means for navigating and editing them. Furthermore, we discuss the efficient and inter-operable serialization and deserialization of such model instances. This approach is evaluated using a scalable benchmark for incremental model editing and the JastAdd RAG system. Our work demonstrates the suitability of RAGs for validating complex and continuously changing models of current software systems. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/ac913939-abe9-4fbb-b2c8-b2609bf40f48
- author
- Mey, Johannes ; Schöne, René ; Hedin, Görel LU ; Söderberg, Emma LU ; Kühn, Thomas ; Fors, Niklas LU ; Öqvist, Jesper LU and Assmann, Uwe
- organization
- publishing date
- 2020-04-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Incremental model evaluation, Bidirectional relations, Reference attribute grammars
- in
- Journal of Computer Languages
- volume
- 57
- publisher
- Elsevier
- external identifiers
-
- scopus:85079355622
- ISSN
- 2590-1184
- DOI
- 10.1016/j.cola.2019.100940
- project
- Bloqqi - ett öppet modulärt automationsspråk
- Säkra mjukvaruuppdateringar för den smarta staden
- ELLIIT LU P05: Scalable Language Tools for Cyber-Physical Systems
- Bloqqi - dubblett - ta bort
- language
- English
- LU publication?
- yes
- id
- ac913939-abe9-4fbb-b2c8-b2609bf40f48
- date added to LUP
- 2020-02-21 10:38:00
- date last changed
- 2022-04-18 20:42:07
@article{ac913939-abe9-4fbb-b2c8-b2609bf40f48, abstract = {{Just like current software systems, conceptual models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated, validated and serialized. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform incremental analysis efficiently using dynamic dependency tracking. However, not all features used in conceptual modelling are directly available in RAGs. In particular, support for noncontainment model relations is only available through encodings. We present an approach called Relational RAGs to directly model uni- and bidirectional noncontainment relations in RAGs and provide efficient means for navigating and editing them. Furthermore, we discuss the efficient and inter-operable serialization and deserialization of such model instances. This approach is evaluated using a scalable benchmark for incremental model editing and the JastAdd RAG system. Our work demonstrates the suitability of RAGs for validating complex and continuously changing models of current software systems.}}, author = {{Mey, Johannes and Schöne, René and Hedin, Görel and Söderberg, Emma and Kühn, Thomas and Fors, Niklas and Öqvist, Jesper and Assmann, Uwe}}, issn = {{2590-1184}}, keywords = {{Incremental model evaluation; Bidirectional relations; Reference attribute grammars}}, language = {{eng}}, month = {{04}}, publisher = {{Elsevier}}, series = {{Journal of Computer Languages}}, title = {{Relational reference attribute grammars: Improving continuous model validation}}, url = {{http://dx.doi.org/10.1016/j.cola.2019.100940}}, doi = {{10.1016/j.cola.2019.100940}}, volume = {{57}}, year = {{2020}}, }