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Creating and Analyzing Source Code Repository Models: A Model-based Approach to Mining Software Repositories

机译:创建和分析源代码存储库模型:基于模型的挖掘软件存储库方法

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With mining software repositories (MSR), we analyze the rich data created during the whole evolution of one or more software projects. One major obstacle in MSR is the heterogeneity and complexity of source code as a data source. With model-based technology in general and reverse engineering in particular, we can use abstraction to overcome this obstacle. But, this raises a new question: can we apply existing reverse engineering frameworks that were designed to create models from a single revision of a software system to analyze all revisions of such a system at once? This paper presents a framework that uses a combination of EMF, the reverse engineering framework Modisco, a NoSQL-based model persistence framework, and OCL-like expressions to create and analyze fully resolved AST-level model representations of whole source code repositories. We evaluated the feasibility of this approach with a series of experiments on the Eclipse code-base.
机译:使用挖掘软件存储库(MSR),我们分析了一个或多个软件项目的整个演变过程中创建的丰富数据。 MSR中的一个主要障碍是作为数据源的源代码的异质性和复杂性。特别是通过基于模型的技术,特别是逆向工程,我们可以使用抽象来克服这个障碍。但是,这提出了一个新问题:我们可以应用现有的逆向工程框架,该框架旨在从软件系统的单一修订版开始创建模型,以分析此类系统的所有修订吗?本文介绍了一种框架,它使用EMF的组合,逆向工程框架模块,基于NoSQL的模型持久框架和ocl的表达式来创建和分析完全解决的整个源代码存储库的模型表示。我们评估了这种方法的可行性,并在Eclipse代码基础上进行了一系列实验。

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