Wrapping LLM generation in a loop that repairs until a production SysMLv2 checker reports zero errors lifts benchmark conformance from 51.16% single-shot to 100%, in at most 8 attempts per case.
Intelligent requirements engineering from natural language and their chaining toward CAD models
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abstract
This paper assumes that design language plays an important role in how designers design and on the creativity of designers. Designers use and develop models as an aid to thinking, a focus for discussion and decision-making and a means of evaluating the reliability of the proposals. This paper proposes an intelligent method for requirements engineering from natural language and their chaining toward CAD models. The transition from linguistic analysis to the representation of engineering requirements consists of the translation of the syntactic structure into semantic form represented by conceptual graphs. Based on the isomorphism between conceptual graphs and predicate logic, a formal language of the specification is proposed. The outcome of this language is chained and translated in Computer Aided Three-Dimensional Interactive Application (CATIA) models. The tool (EGEON: Engineering desiGn sEmantics elabOration and applicatioN) is developed to represent the semantic network of engineering requirements. A case study on the design of a car door hinge is presented to illustrates the proposed method.
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cs.SE 1years
2026 1verdicts
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Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement
Wrapping LLM generation in a loop that repairs until a production SysMLv2 checker reports zero errors lifts benchmark conformance from 51.16% single-shot to 100%, in at most 8 attempts per case.