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An automatic approach for detecting early indicators of design anti-patterns

机译:一种检测设计防模式的早期指标的自动方法

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The paper presents a framework for automatic inferring knowledge about reasons for the appearance of anti-patterns in the program source code during its development. Experiments carried out on histories of development of few open-source java projects shown that we can efficiently detect temporal patterns, which are indicators of likely appearance of future anti-pattern. The approach presented in this paper uses expert knowledge (formal description of anti-patterns) to automatically produce extra knowledge (with machine learning algorithm) about the evolution of bad structures in the program source code. The research can be used to build scalable and adaptive tools, which warns development teams about the fact that system architecture is drifting in the wrong direction, before this is reported by typical static source code analysis tools.
机译:本文介绍了一个框架,用于自动推断出在其开发期间程序源代码中的反模式出现的原因的知识。 关于少数开源Java项目的发展历史记录的实验表明我们可以有效地检测时间模式,这是可能出现未来防模式的指标。 本文呈现的方法使用专家知识(反模式的正式描述),以自动生成关于程序源代码中不良结构的演变的额外知识(具有机器学习算法)。 该研究可用于构建可扩展和自适应工具,警告开发团队关于系统架构在错误的方向上漂移的事实,在典型的静态源代码分析工具报告之前。

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