.png){kind=icon}
返回
Detecting Java software similarities by using different clustering techniques
.png){kind=icon}
OA
AI
DOI：10.1016/j.infsof.2020.106279.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Background: Research on empirical software engineering has increasingly been conducted by analysing and measuring vast amounts of software systems. Hundreds, thousands and even millions of systems have been (and are) considered by researchers, and often within the same study, in order to test theories, demonstrate approaches or run prediction models. A much less investigated aspect is whether the collected metrics might be context-specific, or whether systems should be better analysed in clusters. Objective: The objectives of this study are (i) to define a set of clustering techniques that might be used to group similar software systems, and (ii) to evaluate whether a suite of well-known object-oriented metrics is context-specific, and its values differ along the defined clusters. Method: We group software systems based on three different clustering techniques, and we collect the values of the metrics suite in each cluster. We then test whether clusters are statistically different between each other, using the Kolgomorov-Smirnov (KS) hypothesis testing. Results: Our results show that, for two of the used techniques, the KS null hypothesis (e.g., the clusters come from the same population) is rejected for most of the metrics chosen: the clusters that we extracted, based on application domains, show statistically different structural properties. Conclusions: The implications for researchers can be profound: metrics and their interpretation might be more sensitive to context than acknowledged so far, and application domains represent a promising filter to cluster similar systems.
Keyword:
FOSS (Free and open-source software)
Application Domains
Latent Dirichlet Allocation
Machine Learning
Expert Opinions
OO (object-oriented)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.3
论文数:
3.7K
被引数:
7.7K
机构
引用论文
Critical Re-appraisal of Fluorometric Method for Determination of Selenium in Biological Materials
.png){kind=icon}
PREAI
分享收藏分享收藏An empirical exploration of the distributions of the chidamber and Kemerer object-oriented metrics suite对chidamber和Kemerer面向对象度量套件的分布的实证探索
PREAI
分享收藏
查看更多内容