Model-based generation of natural language specifications
This work addresses the problem of high learning curves in formal languages for software stakeholders, though it appears incremental as it builds on existing controlled language approaches.
The paper tackles the challenge of making formal models more accessible by generating natural language specifications from them, specifically using Attempto Controlled English to produce documentation from basic modeling artifacts like data types and state machines.
Application of formal models provides many benefits for the software and system development, however, the learning curve of formal languages could be a critical factor for an industrial project. Thus, a natural language specification that reflects all the aspects of the formal model might help to understand the model and be especially useful for the stakeholders who do not know the corresponding formal language. Moreover, an automated generation of the documentation from the model would replace manual updates of the documentation for the cases the model is modified. This paper presents an ongoing work on generating natural language specifications from formal models. Our goal is to generate documentation in English from the basic modelling artefacts, such as data types, state machines, and architectural components. To allow further formal analysis of the generated specification, we restrict English to its subset, Attempto Controlled English.