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Model-based test case generation and prioritization: a systematic literature review
Software and Systems Modeling ( IF 2 ) Pub Date : 2021-09-07 , DOI: 10.1007/s10270-021-00924-8
Muhammad Luqman Mohd-Shafie 1 , Wan Mohd Nasir Wan Kadir 1 , Muhammad Khatibsyarbini 1 , Mohd Adham Isa 1 , Horst Lichter 2
Affiliation  

Model-based test case generation (MB-TCG) and prioritization (MB-TCP) utilize models that represent the system under test (SUT) for test generation and prioritization in software testing. They are based on model-based testing (MBT), a technique that facilitates automation in testing. Automated testing is indispensable for testing complex and industrial-size systems because of its advantages over manual testing. In recent years, MB-TCG and MB-TCP publications have shown an encouraging growth. However, the empirical studies done to validate these approaches must not be taken lightly because they reflect the results' validity and whether these approaches are generalizable to the industrial context. This systematic review aims at identifying and reviewing the state-of-the-art for MB-TCG, MB-TCP, and the approaches that combined MB-TCG and MB-TCP. The needs for this review were used to design the research questions. Keywords extracted from the research questions were utilized to search for studies in the literature that will answer the research questions. Prospective studies also underwent a quality assessment to ensure that only studies with sufficient quality were selected. All the research data of this review are also available in a public repository for full transparency. 122 primary studies were finalized and selected. There were 100, 15, and seven studies proposed for MB-TCG, MB-TCP, and MB-TCG and MB-TCP combination approaches, respectively. One of the main findings is that the most common limitations in the existing approaches are the dependency on specifications, the need for manual interventions, and the scalability issue.



中文翻译:

基于模型的测试用例生成和优先级排序:系统文献综述

基于模型的测试用例生成 (MB-TCG) 和优先级排序 (MB-TCP) 利用代表被测系统 (SUT) 的模型在软件测试中进行测试生成和优先级排序。它们基于基于模型的测试 (MBT),这是一种促进测试自动化的技术。自动化测试对于测试复杂和工业规模的系统是必不可少的,因为它优于手动测试。近年来,MB-TCG 和 MB-TCP 出版物显示出令人鼓舞的增长。然而,不能掉以轻心为验证这些方法所做的实证研究,因为它们反映了结果的有效性以及这些方法是否可以推广到工业环境。本系统评价旨在识别和审查 MB-TCG、MB-TCP 以及结合 MB-TCG 和 MB-TCP 的方法的最新技术。本次审查的需要被用来设计研究问题。从研究问题中提取的关键词用于在文献中搜索将回答研究问题的研究。前瞻性研究还进行了质量评估,以确保仅选择具有足够质量的研究。本综述的所有研究数据也可在公共存储库中获得,以实现完全透明。最终确定并选择了 122 项主要研究。分别针对 MB-TCG、MB-TCP 以及 MB-TCG 和 MB-TCP 组合方法提出了 100、15 和 7 项研究。主要发现之一是现有方法中最常见的限制是对规范的依赖、手动干预的需要以及可扩展性问题。

更新日期:2021-09-07
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