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Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution

机译:将功能数据分析应用于开源软件演化研究的机遇与挑战

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摘要

This paper explores the application of functional data analysis (FDA) as a means to study the dynamics of software evolution in the open source context. Several challenges in analyzing the data from software projects are discussed, an approach to overcoming those challenges is described, and preliminary results from the analysis of a sample of open source software (OSS) projects are provided. The results demonstrate the utility of FDA for uncovering and categorizing multiple distinct patterns of evolution in the complexity of OSS projects. These results are promising in that they demonstrate some patterns in which the complexity of software decreased as the software grew in size, a particularly novel result. The paper reports preliminary explorations of factors that may be associated with decreasing complexity patterns in these projects. The paper concludes by describing several next steps for this research project as well as some questions for which more sophisticated analytical techniques may be needed.
机译:本文探讨了功能数据分析(FDA)的应用,以研究开源环境中软件演化的动态。讨论了分析软件项目数据中的几个挑战,描述了克服这些挑战的方法,并提供了对开源软件(OSS)项目样本进行分析的初步结果。结果证明了FDA在OSS项目的复杂性中发现和分类多种不同的演化模式的实用性。这些结果令人鼓舞,因为它们展示了一些模式,其中软件的复杂性随着软件大小的增加而降低,这是一个特别新颖的结果。该论文报告了对这些项目中可能与降低复杂性模式有关的因素的初步探索。本文最后通过描述该研究项目的几个后续步骤以及一些可能需要更复杂的分析技术的问题作总结。

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