1. Towards Queryable and Traceable Domain Models
- Author
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Jörg Kienzle, Gunter Mussbacher, Jin L.C. Guo, and Rijul Saini
- Subjects
0209 industrial biotechnology ,Requirements engineering ,business.industry ,Computer science ,Software development ,A domain ,020207 software engineering ,02 engineering and technology ,Domain model ,Rotation formalisms in three dimensions ,Formalism (philosophy of mathematics) ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,Class diagram ,business ,Software engineering ,Natural language - Abstract
Model-Driven Software Engineering encompasses various modelling formalisms for supporting software development. One such formalism is domain modelling which bridges the gap between requirements expressed in natural language and analyzable and more concise domain models expressed in class diagrams. Due to the lack of modelling skills among novice modellers and time constraints in industrial projects, it is often not possible to build an accurate domain model manually. To address this challenge, we aim to develop an approach to extract domain models from problem descriptions written in natural language by combining rules based on natural language processing with machine learning. As a first step, we report on an automated and tool-supported approach with an accuracy of extracted domain models higher than existing approaches. In addition, the approach generates trace links for each model element of a domain model. The trace links enable novice modellers to execute queries on the extracted domain models to gain insights into the modelling decisions taken for improving their modelling skills. Furthermore, to evaluate our approach, we propose a novel comparison metric and discuss our experimental design. Finally, we present a research agenda detailing research directions and discuss corresponding challenges.
- Published
- 2020