Compiling Static Software Metrics for Reliability and Maintainability from GitHub Repositories

被引:0
|
作者
Ludwig, Jeremy [1 ]
Xu, Steven [1 ]
Webber, Frederick [2 ]
机构
[1] Stottler Henke Associates Inc, San Mateo, CA 94402 USA
[2] Air Force Res Lab, 711th HPW RHAS, Wright Patterson AFB, OH USA
关键词
software product quality; technical debt; reliability; maintainability; architecture; metrics; static code analysis; TECHNICAL DEBT; QUALITY;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:5 / 9
页数:5
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