Semantics of Business Vocabulary and Rules (SBVR) provide a formal framework for representing business rules in a structured and human-readable manner and they have an important role in aligning business logic with enterprise requirements. However, a recent survey has highlighted several limitations in current approaches to SBVR conflict detection and analysis. In this work, we propose a novel approach based on Answer Set Programming (ASP) that addresses most of such limitations as it offers a simple and declarative way of representing SBVR, a set of robust tools for conflict explanation, and high-performance solvers. Moreover, to assess the scalability of our approach, we conducted an experimental analysis using synthetically generated datasets comprising thousands of conflicts.

Representing and Evaluating SBVR Specification via ASP

Dodaro C.;Maratea M.
2025-01-01

Abstract

Semantics of Business Vocabulary and Rules (SBVR) provide a formal framework for representing business rules in a structured and human-readable manner and they have an important role in aligning business logic with enterprise requirements. However, a recent survey has highlighted several limitations in current approaches to SBVR conflict detection and analysis. In this work, we propose a novel approach based on Answer Set Programming (ASP) that addresses most of such limitations as it offers a simple and declarative way of representing SBVR, a set of robust tools for conflict explanation, and high-performance solvers. Moreover, to assess the scalability of our approach, we conducted an experimental analysis using synthetically generated datasets comprising thousands of conflicts.
2025
Answer Set Programming
Controlled Natural Language
Rules
Semantics of Business Vocabulary
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/403420
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