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An Initial Quality Analysis of the Ohloh Software Evolution Data

机译:Ohloh软件演化数据的初始质量分析

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Large public data sets on software evolution promise great value to both researchers and practitioners, in particular for software (development) analytics. To realise this value, the data quality of such data sets needs to be studied and improved. Despite these data sets being of a secondary nature, i.e., they were not collected by the people using them, data quality is often taken for granted, casting doubt on conclusions drawn from those data. This paper reports on an intial investigation of the quality of the software evolution data available on Ohloh, and further describes steps taken to cleanse the data set. Our goal is that other researchers, practitioners, and parties responsible for data sets such as Ohloh, use the outcomes of the validation and cleansing steps to improve quality of data sets in the public domain.
机译:关于软件演化的大型公共数据集对研究人员和从业人员都具有巨大的价值,特别是对于软件(开发)分析而言。为了实现此值,需要研究和改进此类数据集的数据质量。尽管这些数据集是次要的,即不是由使用它们的人收集的,但数据质量通常被认为是理所当然的,这使人们对从这些数据得出的结论产生怀疑。本文报告了对Ohloh上可用的软件演进数据质量的初步调查,并进一步描述了清理数据集所采取的步骤。我们的目标是其他负责数据集的研究人员,从业人员和当事方(例如Ohloh)使用验证和清理步骤的结果来提高公共领域数据集的质量。

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