Exploranative Code Quality Documents
Exploranative Code Quality Documents
复制标题
解释性代码质量文档
DOI：
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发表时间：
2019
影响因子：
5.2
通讯作者：
D. Weiskopf
中科院分区：
文献类型：
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作者：
Haris Mumtaz;Shahid Latif;Fabian Beck;D. Weiskopf
良好的代码质量是高效开发可维护软件的先决条件。在本文中，我们提出了一种新的方法来生成探索性（解释性和探索性）的数据驱动的文档，报告代码质量在一个互动的，探索性的环境。我们采用基于模板的自然语言生成方法来创建有关代码质量的文本解释，依赖于软件度量数据。交互式文档通过不同类型的可视化来丰富，包括用于数据探索的平行坐标图和散点图以及嵌入到文本中的图形。我们设计了一个交互模型，允许用户探索代码质量与文本和可视化之间的一致链接;通过集成的解释性文本，用户被教导有关代码质量方面的背景知识。我们的交互式文档方法是在设计研究过程中开发的，其中包括软件工程和视觉分析专家。虽然解决方案是特定于软件工程场景，我们讨论如何将概念推广到多变量数据，并在更广泛的范围内报告经验教训。
Good code quality is a prerequisite for efficiently developing maintainable software. In this paper, we present a novel approach to generate exploranative (explanatory and exploratory) data-driven documents that report code quality in an interactive, exploratory environment. We employ a template-based natural language generation method to create textual explanations about the code quality, dependent on data from software metrics. The interactive document is enriched by different kinds of visualization, including parallel coordinates plots and scatterplots for data exploration and graphics embedded into text. We devise an interaction model that allows users to explore code quality with consistent linking between text and visualizations; through integrated explanatory text, users are taught background knowledge about code quality aspects. Our approach to interactive documents was developed in a design study process that included software engineering and visual analytics experts. Although the solution is specific to the software engineering scenario, we discuss how the concept could generalize to multivariate data and report lessons learned in a broader scope.
DOI：
10.1109/tvcg.2018.2865145
发表时间：
2019-01
影响因子：
5.2
作者：
Arjun Srinivasan;S. Drucker;A. Endert;J. Stasko
通讯作者：
Arjun Srinivasan;S. Drucker;A. Endert;J. Stasko