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Compiling static software metrics for reliability and maintainability from GitHub repositories

机译:从GitHub存储库编译静态软件指标以确保可靠性和可维护性

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This paper identifies a small, essential set of static software code metrics linked to the software product quality characteristics of reliability and maintainability and to the most commonly identified sources of technical debt. A plug-in is created for the Understand code visualization and static analysis tool that calculates and aggregates the metrics. The plug-in produces a high-level interactive html report as well as developer-level information needed to address quality issues using Understand. A script makes use of Git, Understand, and the plug-in to compile results for a list of GitHub repositories into a single file. The primary contribution of this work is to describe an open-source plug-in to measure and visualize architectural complexity based on the propagation cost and core size metrics, which are not currently found in other tools. The plug-in should be useful to researchers and practitioners interested in these two metrics and as an expedient starting point to experimentation with metric collection and aggregation for groups of GitHub repositories. The plug-in was developed as a first step in an ongoing project aimed at applying case-based reasoning to the issue of software product quality.
机译:本文确定了一小部分基本的静态软件代码指标,这些指标与软件产品的可靠性和可维护性质量特征以及最常见的技术债务来源有关。为理解代码可视化和静态分析工具创建了一个插件,用于计算和汇总指标。该插件会生成高级交互式html报告以及使用Understand解决质量问题所需的开发人员级别的信息。脚本利用​​Git,Understand和插件将GitHub存储库列表的结果编译为单个文件。这项工作的主要贡献是描述了一个开源插件,该插件可以基于传播成本和核心大小度量标准来度量和可视化体系结构的复杂性,而其他工具目前还找不到这些插件。对于对这两个指标感兴趣的研究人员和实践者,该插件应该是有用的,并且可以作为对GitHub存储库组进行指标收集和聚合实验的便利起点。该插件的开发是正在进行的项目的第一步,该项目旨在将基于案例的推理应用于软件产品质量问题。

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