Business Rules: From Text to Formal Language

Business rules are fundamental to organizational consistency and decision-making, but their natural language format often leads to misunderstandings and inconsistencies. This chapter addresses this challenge by presenting a novel method for automating the translation of business rules from natural language to formal statements. The approach leverages the Semantic of Business Vocabulary and Rules (SBVR) standard as an intermediate model, ensuring that business rules are both human-understandable and machine-interpretable. The chapter begins with an overview of the SBVR standard, highlighting its role in bridging the gap between users and machines. It then delves into a survey of current methodologies for transforming textual specifications into formal language, providing a comprehensive background for the proposed approach. The core of the chapter details the automated method for translating textual business rules into formal statements, using a model-to-model transformation. This method involves extracting components from textual business rules, mapping them to the SBVR metamodel, and finally translating the SBVR elements into a formal language. The chapter also discusses the mapping rules for various SBVR elements, such as noun concepts, verb concepts, and logical formulations, providing clear examples to illustrate the translation process. By automating the translation of business rules, this approach aims to improve accuracy, minimize misunderstandings, and encourage consistent comprehension of business rules, ultimately enhancing organizational decision-making and software requirements.