ARSENAL: Automatic Requirements Specification Extraction from Natural Language
This addresses the challenge of automating requirements specification for critical systems, enabling more efficient design, testing, and verification processes.
The paper tackles the problem of transforming informal natural language requirements into formal models for analysis, presenting ARSENAL as a framework that systematically converts these requirements into analyzable logic specifications to check for consistency and implementability.
Requirements are informal and semi-formal descriptions of the expected behavior of a complex system from the viewpoints of its stakeholders (customers, users, operators, designers, and engineers). However, for the purpose of design, testing, and verification for critical systems, we can transform requirements into formal models that can be analyzed automatically. ARSENAL is a framework and methodology for systematically transforming natural language (NL) requirements into analyzable formal models and logic specifications. These models can be analyzed for consistency and implementability. The ARSENAL methodology is specialized to individual domains, but the approach is general enough to be adapted to new domains.