Dataflow graphs as complete causal graphs

Andrei Paleyes, Siyuan Guo, B. Scholkopf, Neil D. Lawrence
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引用次数: 2

Abstract

Component-based development is one of the core principles behind modern software engineering practices. Understanding of causal relationships between components of a software system can yield significant benefits to developers. Yet modern software design approaches make it difficult to track and discover such relationships at system scale, which leads to growing intellectual debt. In this paper we consider an alternative approach to software design, flow-based programming (FBP), and draw the attention of the community to the connection between dataflow graphs produced by FBP and structural causal models. With expository examples we show how this connection can be leveraged to improve day-to-day tasks in software projects, including fault localisation, business analysis and experimentation.
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数据流图作为完整的因果图
基于组件的开发是现代软件工程实践背后的核心原则之一。了解软件系统组件之间的因果关系可以为开发人员带来巨大的好处。然而,现代软件设计方法使得很难在系统规模上跟踪和发现这种关系,这导致了不断增长的智力债务。在本文中,我们考虑了软件设计的另一种方法,基于流的编程(flow-based programming, FBP),并提请社区注意由FBP生成的数据流图与结构因果模型之间的联系。通过说明性的例子,我们展示了如何利用这种联系来改进软件项目中的日常任务,包括故障定位、业务分析和实验。
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