Complete and accurate clone detection in graph-based models
Complete and accurate clone detection in graph-based models
复制标题
基于图的模型中完整且准确的克隆检测
DOI：
--
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
T. Nguyen
中科院分区：
文献类型：
--
作者：
N. Pham;H. Nguyen;T. Nguyen;Jafar M. Al;T. Nguyen
模型驱动工程（MDE）已成为许多大型软件的重要开发框架。先前的研究报告称，与传统的基于代码的开发一样，克隆在MDE中也会出现。然而，由于在检测精度和完整性方面存在局限性，针对模型中的克隆检测工作很少。本文介绍了ModelCD，这是一种用于Matlab/Simulink模型的新型克隆检测工具，它能够高效、准确地检测完全匹配和近似的模型克隆。ModelCD的核心是两种基于图的新型克隆检测算法，它们能够系统地、渐进地发现具有高度完整性、准确性和可扩展性的克隆。我们对许多实际系统进行了各种实验研究的实证评估，以证明我们方法的有效性，并将ModelCD的性能与现有工具进行比较。
Model-Driven Engineering (MDE) has become an important development framework for many large-scale software. Previous research has reported that as in traditional code-based development, cloning also occurs in MDE. However, there has been little work on clone detection in models with the limitations on detection precision and completeness. This paper presents ModelCD, a novel clone detection tool for Matlab/Simulink models, that is able to efficiently and accurately detect both exactly matched and approximate model clones. The core of ModelCD is two novel graph-based clone detection algorithms that are able to systematically and incrementally discover clones with a high degree of completeness, accuracy, and scalability. We have conducted an empirical evaluation with various experimental studies on many real-world systems to demonstrate the usefulness of our approach and to compare the performance of ModelCD with existing tools.