A Domain Analysis of Data Structure and Algorithm Explanations in the Wild
A Domain Analysis of Data Structure and Algorithm Explanations in the Wild
复制标题
数据结构领域分析和算法解释
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Eric Walkingshaw
中科院分区：
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作者：
J. M. Young;Eric Walkingshaw
数据结构和算法的解释是几种符号的复杂交互，包括自然语言、数学、伪代码和图表。目前，这样的解释是使用各种工具临时创建的，所产生的构件是静态的，这降低了解释价值。我们设想了一种特定于领域的语言，用于开发丰富的、交互的数据结构和算法解释。在本文中，我们分析了这个领域，以勾勒出对我们的语言的需求。我们执行扎根的理论分析，以生成在线收集的解释构件的定性编码系统。该编码系统暗示了算法和数据结构的解释之间的共同结构。我们相信这个结构可以被重用为创建交互解释构件的特定于领域的语言的语义基础。这项工作是我们开发面向解释的编程范例的努力的一部分，该范例将编程的重点从计算结果转移到对这些结果是如何计算的进行丰富的解释。
Explanations of data structures and algorithms are complex interactions of several notations, including natural language, mathematics, pseudocode, and diagrams. Currently, such explanations are created ad hoc using a variety of tools and the resulting artifacts are static, reducing explanatory value. We envision a domain-specific language for developing rich, interactive explanations of data structures and algorithms. In this paper, we analyze this domain to sketch requirements for our language. We perform a grounded theory analysis to generate a qualitative coding system for explanation artifacts collected online. This coding system implies a common structure among explanations of algorithms and data structures. We believe this structure can be reused as the semantic basis of a domain-specific language for creating interactive explanation artifacts. This work is part of our effort to develop the paradigm of explanation-oriented programming, which shifts the focus of programming from computing results to producing rich explanations of how those results were computed.