A UML Activity Flow Graph-Based Regression Testing Approach

Author:

Jha Pragya12ORCID,Sahu Madhusmita1,Isobe Takanori2

Affiliation:

1. Department of Computer Science and Engineering, C. V. Raman Global University, Bhubaneswar 752054, India

2. Graduate School of Information Sciences, University of Hyogo, Kobe 650-0047, Japan

Abstract

Regression testing is a crucial process that ensures that changes made to a system do not affect existing functionalities. However, there is currently no adequate technique for selecting test cases that consider changes in Unified Modeling Language (UML) activity flow graphs. This paper proposes a novel approach to regression testing of UML diagrams, focusing on healthcare management systems. We provide a formal definition of sequence and activity diagrams and their relationship and construct corresponding activity flow graphs, which are used to develop a regression testing algorithm. The proposed algorithm categorizes test cases into reusable, retestable, obsolete, and newly generated categories by comparing old and new versions of UML activity flow graphs. The methodology is evaluated using a custom-designed hospital management system website as the test case, and the results demonstrate a significant reduction in time and resources required for regression testing. Our study provides valuable insights into the application of UML diagrams and activity flow graphs in regression testing, making it an important contribution to software testing research.

Funder

JST, PRESTO

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 2 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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3