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Implementation of Analytical Hierarchy Process in Detecting Structural Code Clones

机译:层次分析法在结构代码克隆检测中的实现

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The nature and the size of data plays an important rule at the identification process of similar objects (clones). The type of utilized similarity measures is also an important factor. The nature of data and selecting the right identification algorithm appropriate to type of data should be examined thoroughly when a clone identification technique is applied. This study suggests a new methodology in software systems for minimization/prevention of code cloning. Its main contribution is to propose an Analytical Hierarchy Process based methodology at detection of code clones in object-oriented software systems, in which the software is represented by means of software metrics data at class level. The suggested clone detection model is able to select the most suitable code clone candidates by considering different correlation and distance metrics to identify code clones. To facilitate the testing and the usability of the suggested clone detection model, the system is used for detection of structural code clone. The methodology is validated by comparison with results obtained by human judges as well as by comparison with a plain structural code clone identification approach. The evaluation of the methodology is carried out in terms of accuracy and indicates promising results.
机译:数据的性质和大小在相似对象(克隆)的识别过程中起着重要的规则。所使用的相似性度量的类型也是一个重要因素。当使用克隆识别技术时,应彻底检查数据的性质和选择适合数据类型的正确识别算法。这项研究提出了一种软件系统中用于最小化/防止代码克隆的新方法。它的主要贡献是提出了一种基于层次分析法的方法,用于检测面向对象软件系统中的代码克隆,其中该软件由类级别的软件指标数据表示。建议的克隆检测模型能够通过考虑不同的相关性和距离度量来识别代码克隆,从而选择最合适的代码克隆候选。为了便于测试和建议的克隆检测模型的可用性,该系统用于检测结构代码克隆。通过与人类法官获得的结果进行比较以及与普通结构代码克隆识别方法进行比较,验证了该方法。该方法学的评估是在准确性方面进行的,并表明了令人鼓舞的结果。

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