Combining type inference techniques for semi-automatic UML generation from Pharo code

IF 1.7 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Journal of Computer Languages Pub Date : 2024-11-14 DOI:10.1016/j.cola.2024.101300
Jan Blizničenko, Robert Pergl
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Abstract

This paper explores how to reconstruct UML diagrams from dynamically typed languages such as Smalltalk, which do not use explicit type information. This lack of information makes traditional methods for extracting associations difficult. It addresses the need for automated techniques, particularly in legacy software systems, to facilitate their transformation into modern technologies, focusing on Smalltalk as a case study due to its extensive industrial legacy and modern adaptations like Pharo. We propose a way to create UML diagrams from Smalltalk code, focusing on using type inference to determine UML associations. For optimal outcomes for large-scale software systems, we recommend combining different type inference methods in an automatic or semi-automatic way.
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结合类型推断技术,从 Pharo 代码中半自动生成 UML
本文探讨了如何从动态类型语言(如 Smalltalk)中重建 UML 图表,因为这种语言不使用显式类型信息。这种信息的缺乏使得提取关联的传统方法变得困难。本文以Smalltalk为例,探讨了对自动化技术的需求,特别是在传统软件系统中,以促进其向现代技术的转化。我们提出了一种从Smalltalk代码中创建UML图表的方法,重点是使用类型推论来确定UML关联。为了使大型软件系统达到最佳效果,我们建议以自动或半自动的方式结合不同的类型推断方法。
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来源期刊
Journal of Computer Languages
Journal of Computer Languages Computer Science-Computer Networks and Communications
CiteScore
5.00
自引率
13.60%
发文量
36
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