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Underproduction: An Approach for Measuring Risk in Open Source Software

机译:弱势型:衡量开源软件风险的方法

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The widespread adoption of Free/Libre and Open Source Software (FLOSS) means that the ongoing maintenance of many widely used software components relies on the collaborative effort of volunteers who set their own priorities and choose their own tasks. We argue that this has created a new form of risk that we call ‘underproduction' which occurs when the supply of software engineering labor becomes out of alignment with the demand of people who rely on the software produced. We present a conceptual framework for identifying relative underproduction in software as well as a statistical method for applying our framework to a comprehensive dataset from the Debian GNU/Linux distribution that includes 21,902 source packages and the full history of 461,656 bugs. We draw on this application to present two experiments: (1) a demonstration of how our technique can be used to identify at-risk software packages in a large FLOSS repository and (2) a validation of these results using an alternate indicator of package risk. Our analysis demonstrates both the utility of our approach and reveals the existence of widespread underproduction in a range of widely-installed software components in Debian.
机译:自由/ Libre和开源软件(磁芯)的广泛采用意味着许多广泛使用的软件组件的持续维护依赖于设置自己优先级并选择自己任务的志愿者的协作工作。我们认为,这创造了一种新的风险,我们称之为“展示的潜力量”,当软件工程劳动力的供应变得与依赖于所产生的软件的人们的需求转移时发生。我们提出了一种概念框架,用于识别软件中的相对漏报库以及从Debian GNU / Linux发行版中将框架应用于一个全面数据集的统计方法,其中包括21,902个源包和461,656个错误的完整历史记录。我们绘制此应用程序呈现两个实验:(1)示范如何使用我们的技术在大型牙线存储库中识别风险软件包,并使用备用封装风险指标验证这些结果。我们的分析显示了我们的方法的效用,并揭示了Debian中一系列广泛安装的软件组件中广泛展望的存在。

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