ARSENAL: Automatic Requirements Specification Extraction from Natural Language

TL;DR

ARSENAL is a framework that automatically converts natural language requirements into formal models for analysis, enhancing consistency and implementability checks across various domains.

Contribution

It introduces a systematic methodology for transforming natural language requirements into formal models, adaptable to different domains.

Findings

Enables automatic analysis of requirements for consistency.

Supports domain-specific customization of the transformation process.

Facilitates formal verification of system requirements.

Abstract

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.