DoMoBOT: A Modelling Bot for Automated and Traceable Domain Modelling

Rijul Saini, G. Mussbacher, Jin L. C. Guo, J. Kienzle
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引用次数: 2

Abstract

In the initial phases of the software development cycle, domain modelling is typically performed to transform informal requirements expressed in natural language into concise and analyzable domain models. These models capture the key concepts of an application domain and their relationships in the form of class diagrams. Building domain models manually is often a time-consuming and labor-intensive task. The current approaches which aim to extract domain models automatically, are inadequate in providing insights into the modelling decisions taken by extractor systems. This inhibits modellers to quickly confirm the completeness and conciseness of extracted domain models. To address these challenges, we present DoMoBOT, a domain modelling bot that uses a traceability knowledge graph to enable traceability of modelling decisions from extracted domain model elements to requirements and vice-versa. In this tool demo paper, we showcase how the implementation and architecture of DoMoBOT facilitate modellers to extract domain models and gain insights into the modelling decisions taken by our bot.
DoMoBOT:一个用于自动化和可追溯领域建模的建模机器人
在软件开发周期的初始阶段,通常执行领域建模以将用自然语言表达的非正式需求转换为简洁且可分析的领域模型。这些模型以类图的形式捕获应用程序领域的关键概念及其关系。手动构建领域模型通常是一项耗时且劳动密集型的任务。当前旨在自动提取领域模型的方法,在提供对提取器系统所采取的建模决策的见解方面是不足的。这阻碍了建模者快速确认提取的领域模型的完整性和简洁性。为了解决这些挑战,我们提出了DoMoBOT,一个领域建模机器人,它使用可追溯性知识图来实现从提取的领域模型元素到需求的建模决策的可追溯性,反之亦然。在这篇工具演示论文中,我们展示了DoMoBOT的实现和体系结构如何帮助建模者提取领域模型,并深入了解我们的bot所做的建模决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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