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Sequence Data Mining Approach for Detecting Type-3 Clones

机译:用于检测3型克隆的序列数据挖掘方法

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Code clones are introduced to source code by changing, adding, and/or deleting statements in copied code fragments. Thus, the problem of finding code clones is essentially the detection of strings that partially match. The proposed algorithm is based on the well-known apriori principle in data mining and is tailored to detect code clones represented as sequences of strings. However, the apriori principle may generate too many sequential patterns. The proposed algorithm finds a compact representation of sequential patterns, known as maximal frequent sequential patterns, which is often two orders of magnitude smaller than frequent sequential patterns. Early experiments using the Java SDK 1.7.0.45 lang package demonstrate the number of extracted patterns and elapsed time in several contexts.
机译:代码克隆通过在复制的代码片段中更改,添加和/或删除语句来引入源代码。因此,查找代码克隆的问题基本上是部分匹配的字符串的检测。所提出的算法基于数据挖掘中的众所周知的APRIORI原理,并定制以检测表示为弦序列的码克隆。但是,Apriori原理可能会产生太多连续模式。所提出的算法发现了顺序模式的紧凑表示,称为最大频繁顺序图案,其通常比频繁顺序图案小的两个数量级。使用Java SDK 1.7.0.45的早期实验朗包展示了几种情况下提取的模式和经过时间的数量。

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