论文标题
通过github和stackoverflow上的社区特征分析编程语言
Analyzing programming languages by community characteristics on Github and StackOverflow
论文作者
论文摘要
编程语言的选择是一个非常重要的决定，因为它不仅会影响软件的性能和可维护性，而且决定了人才库和社区支持。为了更好地了解做出这样决定所涉及的权衡，我们通过在线协作平台定义和计算编程语言的普及，需求，可用性和社区参与。我们使用GitHub和Stackoverflow的数据（两个最受欢迎的编程社区）进行分析。我们从GitHub获得了与数据相关的项目，语言和开发人员参与，并提供了带有答案的编程问题以及Stackoverflow的语言标签。我们分别计算两个数据源的指标，然后结合指标，为最受欢迎的编程语言提供社区的整体和强大图片。
The choice of programming language is a very important decision as it not only affects the performance and maintainability of the software but also dictates the talent pool and community support available. To better understand the trade-offs involved in making such a decision, we define and compute popularity, demand, availability and community engagement of programming languages through online collaboration platforms. We perform our analysis using data from Github and StackOverflow, two of the most popular programming communities. We get data related projects, languages and developer engagement from Github and programming questions with answers along with language tags from StackOverflow. We compute metrics separately for the two data sources and then combine the metrics to provide a holistic and robust picture of the communities for the most popular programming languages.
