需求工程中用例视图的缺陷检测技术

Poranat Tianual, A. Pohthong
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引用次数: 2

摘要

在过去的十年中,面向对象的软件工程(OOSE)受到了许多软件开发人员的欢迎,特别是使用统一建模语言(UML)的OOSE。在分析阶段,用例视图经常在大多数系统中使用。这些视图显示了与系统涉众相关的系统功能。因此,用例视图似乎是软件系统的基石。用例视图中出现的缺陷将影响以后的设计。如果能及早发现这些缺陷,将节省软件开发的时间和成本。因此,本研究提出了一种在分析阶段或需求工程过程中检测用例视图缺陷的技术。正确的用户需求以传统的基于表单的方式创建为需求规范,用于测试比较。提出了基于表单的需求和UML用例规范生成决策表的算法以及用例视图验证的算法。调查了两个简单的案例,并将其作为初步评价。为了比较人工故障检测和我们提出的自动故障检测系统,我们选择了十九名四年级学生作为初步调查的对象。他们被要求为每个案例研究执行四项任务。结果表明,在两个案例中,人工故障检测的效率分别为47%和44%,总体平均为45.5%。目前,我们将该技术应用于更复杂的工业环境和软件工程师熟悉的软件系统。
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Defects Detection Technique of Use Case Views during Requirements Engineering
In the past decade, object-oriented software engineering (OOSE) has gained popularity from many software developers, especially OOSE with a unified modeling language (UML). Use case views are often used in most systems during an analysis phase. These views show the system functionality related to the system stakeholders. Hence, use case views seem to be a corner stone for a software system. The defects occurring in use case views will affect the later designs. If these defects can be found early, it would save time and cost in software development. Therefore, this research proposes a technique for detecting defects in use case views during an analysis phase or requirements engineering process. Correct users' requirements were created as requirements specifications in a traditional form-based style for testing comparison. The algorithms for generating decision table from form-based requirements and UML use case specification as well as the algorithm for use case view validation were invented. Two simple case studies were investigated and used as the preliminary evaluation. The nineteen fourth-year students were selected as the subjects for the preliminary investigation in order to compare between manual fault detection and our automated proposed system. They were asked to perform four tasks for each case study. The results show that the efficiency of manual fault detection is less than the proposed technique at 47% and 44% or overall average as 45.5% for the two case studies. Currently, we apply this proposed technique to more complex industrial setting and familiar software systems to software engineers.
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