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Summary of an article: Data Mining in the Detection of Higher Level Clones in Software Name Institution Data Mining in the Detection of Higher Level Clones in Software This article dwells on code clone which involves similar program structures that have a considerable size as well as significant similarity. According to Basit and Jarzabek (2009), knowing the clone’s location can assist one in comprehending the structure and for maintenance efforts. It is important to remove clones to evade their harmful impacts. Some of the methods that can be used include refactoring, replacing them with function macros and calls, or utilize unconventional metalevel approaches like Aspect-oriented programming and XVCL. Basit and Jarzabek (2009) argue that the limitation of clone detection is a big problem that software developers experience since many researchers are engrossed by the duplicate code fragments or the simple clones instead of focusing on the bigger picture whereby the duplicated codes can be a part of a big replicated program. As such, they are known as larger granularity similarities clones. Most of the cloning is found within the system variants that originates from the common base code that is during the evolution process. This occurs due to the excessive copying as well as modification of the program files hence the clones either larger or small occur in the system variants. Basit and Jarzabek (2009) assert that the knowledge of structural cloning is prevalent during the creation, but the community lacks formal ways of making the presence of structural clone visible within software other than the utilization of naming conventions and the documentation

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