Automated change impact analysis between SysML models of requirements and design

S. Nejati, M. Sabetzadeh, Chetan Arora, L. Briand, Felix Mandoux
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引用次数: 22

Abstract

An important activity in systems engineering is analyzing how a change in requirements will impact the design of a system. Performing this analysis manually is expensive, particularly for complex systems. In this paper, we propose an approach to automatically identify the impact of requirements changes on system design, when the requirements and design elements are expressed using models. We ground our approach on the Systems Modeling Language (SysML) due to SysML's increasing use in industrial applications. Our approach has two steps: For a given change, we first apply a static slicing algorithm to extract an estimated set of impacted model elements. Next, we rank the elements of the resulting set according to a quantitative measure designed to predict how likely it is for each element to be impacted. The measure is computed using Natural Language Processing (NLP) applied to the textual content of the elements. Engineers can then inspect the ranked list of elements and identify those that are actually impacted. We evaluate our approach on an industrial case study with 16 real-world requirements changes. Our results suggest that, using our approach, engineers need to inspect on average only 4.8% of the entire design in order to identify the actually-impacted elements. We further show that our results consistently improve when our analysis takes into account both structural and behavioral diagrams rather than only structural ones, and the natural-language content of the diagrams in addition to only their structural and behavioral content.
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需求和设计的SysML模型之间的自动变更影响分析
系统工程中的一个重要活动是分析需求的变化将如何影响系统的设计。手动执行这种分析是昂贵的,特别是对于复杂的系统。在本文中,我们提出了一种方法来自动识别需求变化对系统设计的影响,当需求和设计元素使用模型表示时。我们的方法基于系统建模语言(SysML),因为SysML在工业应用程序中的使用越来越多。我们的方法有两个步骤:对于给定的更改,我们首先应用静态切片算法来提取受影响模型元素的估计集。接下来,我们根据定量度量来对结果集中的元素进行排序,该度量旨在预测每个元素受到影响的可能性。该度量是使用应用于元素文本内容的自然语言处理(NLP)计算的。然后工程师可以检查元素的排序列表,并确定那些实际受到影响的元素。我们在一个包含16个真实需求变化的工业案例研究中评估了我们的方法。我们的结果表明,使用我们的方法,工程师平均只需要检查整个设计的4.8%,以确定实际受影响的元素。我们进一步表明,当我们的分析考虑到结构图和行为图而不仅仅是结构图,以及图的自然语言内容以及它们的结构和行为内容时,我们的结果会持续改进。
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