Leveraging SPARQL Queries for UML Consistency Checking

Author:

Wei Bingyang1,Sun Jing2

Affiliation:

1. Department of Computer Science, Texas Christian University, Fort Worth TX, USA

2. Department of Computer Science, The University of Auckland, Auckland, New Zealand

Abstract

Context and motivation: Multiple-viewed requirements modeling method describes the system to-be from different perspectives. Some requirements models are then specified in various UML diagrams. Question/problem: Managing those models can be tedious and error-prone, since a lot of CASE tools provide poor support for reasoning and consistency checking. Principal ideas/results: Ontology is a formal notation for describing concepts and their relations in a domain. Since software requirements are a kind of knowledge, we propose to adopt a knowledge engineering approach for managing the consistency of requirements models. In this paper, an ontology for three most commonly used UML diagrams is developed in Web Ontology Language (OWL). The transformation of UML class, sequence and state diagrams to OWL knowledge base is presented. Owing to the underlying logical reasoning capability of OWL, a semantic query language, SPARQL (SPARQL Protocol and RDF Query Language), is used to query the knowledge base for consistency checking. Contribution: This paper introduces a semantic web-based knowledge engineering approach to represent and manage software requirements knowledge in OWL. By experimenting with a concrete software system, we demonstrate the feasibility and applicability of this knowledge approach.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Incremental-concurrent fusion checking for efficient context consistency;Journal of Systems and Software;2024-01

2. Complex SPARQL Queries Based on Ontology and RDF;Proceedings of the 4th International Conference on Big Data Analytics for Cyber-Physical System in Smart City - Volume 1;2023

3. INFuse: Towards Efficient Context Consistency by Incremental-Concurrent Check Fusion;2022 IEEE International Conference on Software Maintenance and Evolution (ICSME);2022-10

4. Representing BORM Process Models using OWL and RDF;Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management;2021

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