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Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

Beyond Low-Code Development: Marrying Requirements Models and Knowledge Representations


DOI: http://dx.doi.org/10.15439/2022F129

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 919928 ()

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Abstract. Typical Low-Code Development platforms enable model-driven generation of web applications from high-level visual notations. They normally express the UI and the application logic, which allows generating the frontend and basic CRUD operations. However, more complex domain logic (data processing) operations still necessitate the use of traditional programming. This paper proposes a new visual language, called RSL-DL, to represent domain knowledge with complex domain rules aligned with requirements models. The language synthesises and extends approaches found in knowledge representation (ontologies) and software modelling language engineering. Its purpose is to enable a fully automatic generation of domain logic code by reasoning over and reusing domain knowledge. The language's abstract syntax is defined using a meta-model expressed in MOF. Its semantics is expressed with several translational rules that map RSL-DL models onto typical programming language constructs. The rules are explained informally in natural language and formalised using a graphical transformation notation. It is also supported by introducing an inference engine that enables processing queries to domain models and selecting appropriate invocations to generated code. The presented language was implemented by building a dedicated model editor and transformation engine. It was also initially validated through usability studies. Based on these results, we conclude that declarative knowledge representations can be successfully used to produce imperative back-end code with non-trivial logic.


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