Test Co-Evolution in Software Projects: A Large-Scale Empirical Study

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Charles Miranda, Guilherme Avelino, Pedro Santos Neto
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引用次数: 0

Abstract

The asynchronous evolution of tests and code can compromise software quality and project longevity. To investigate the impact of test and production code co-evolution, this study analyzes a large-scale dataset of 526 GitHub repositories written in six programming languages: JavaScript, TypeScript, Java, Python, PHP, and C#. We focus on understanding how tests evolve throughout the software lifecycle and the frequency with which production and test code evolve in sync. By applying clustering algorithms and Pearson's correlation coefficient, we identify different patterns of test co-evolution between projects. We found a significant correlation between high test co-evolution and smaller development teams but no significant relationship with the frequency of different maintenance activities (corrective, adaptive, perfective, or multi). Despite this, we identified five distinct test evolution patterns, highlighting diverse approaches to integrating testing practices. This work provides valuable insights into the dynamics of test co-evolution and its correlation in software maintainability.

Abstract Image

软件项目中的测试协同进化:一个大规模的实证研究
测试和代码的异步发展会损害软件质量和项目寿命。为了研究测试和生产代码协同进化的影响,本研究分析了526个GitHub存储库的大规模数据集,这些存储库使用六种编程语言编写:JavaScript、TypeScript、Java、Python、PHP和c#。我们关注于理解测试是如何在整个软件生命周期中发展的,以及生产和测试代码同步发展的频率。运用聚类算法和Pearson相关系数,识别项目间测试协同进化的不同模式。我们发现在高测试协同进化和较小的开发团队之间存在重要的相关性,但是与不同维护活动(纠正性的、适应性的、完美的或多重的)的频率之间没有重要的关系。尽管如此,我们确定了五种不同的测试演变模式,强调了集成测试实践的不同方法。这项工作为测试协同进化的动态及其在软件可维护性中的相关性提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Software-Evolution and Process
Journal of Software-Evolution and Process COMPUTER SCIENCE, SOFTWARE ENGINEERING-
自引率
10.00%
发文量
109
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