一种有效的开源存储库增量分析算法

Zhanyu Yang, Fu Xu, Zhibo Chen, Yu Sun
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引用次数: 0

摘要

挖掘代码库是软件工程中检测开源代码重用的重要实践。针对现有的分析算法无法满足高效大规模开源分析的要求,本文提出了一种有效的增量分析算法,通过对比代码库中的快照提取增量文本修改,然后通过映射算法将上述文本修改转化为增量函数。同时,提出了一种针对增量函数的指纹算法,实现了函数间的高效比较。实验表明,增量分析算法在处理大规模代码时,具有存储空间小、分析速度快等优点,优于传统的增量分析算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Effective Incremental Analysis Algorithm of Open Source Repository
Mining code repositories is a significant practice to detect the reuse of open source code in software engineering. As the existing analysis algorithms fail to meet the requirements of efficient large-scale open source analysis, this paper proposes an effective incremental analysis algorithm that can extract incremental text modifications by comparing snapshots in code repositories and then transform the above-mentioned text modifications into incremental functions through the application of mapping algorithm. Meanwhile, a fingerprint algorithm targeting incremental functions is put forward for efficient comparisons of functions. The experiments indicate that when dealing with large-scale code, the incremental analysis algorithm outperforms the traditional ones with less storage space and faster analysis speed.
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