Developing controlled natural language for formal specification patterns using AI assistants
This work addresses the challenge of translating formal specifications into natural language for requirements engineering, but it appears incremental as it builds on existing formal patterns and AI techniques.
The researchers tackled the problem of constructing controlled natural language for formal specification patterns by developing a method using an AI assistant, which was tested on event-driven temporal requirements.
Using an AI assistant, we developed a method for systematically constructing controlled natural language for requirements based on formal specification patterns containing logical attributes. The method involves three stages: 1) compiling a generalized natural language requirement pattern that utilizes all attributes of the formal specification template; 2) generating, using the AI assistant, a corpus of natural language requirement patterns, reduced by partially evaluating attributes (the developed prompt utilizes the generalized template, attribute definitions, and specific formal semantics of the requirement patterns); and 3) formalizing the syntax of the controlled natural language based on an analysis of the grammatical structure of the resulting patterns. The method has been tested for event-driven temporal requirements.