CAJ | 학술논문

如何有效地检测程序设计课程作业中的抄袭现象是一个重要的问题.传统的抄袭检测方法主要利用代码的属性或结构信息来度量代码之间的相似性.给出了一种基于误差反向传播(BP算法)多层前向神经网络的代码抄袭检测方法.提取程序之间的7种比较特征作为神经网络的输入,经过网络计算后得出程序的相似值,并将该值与抄袭决策阈值相比较以判定存在抄袭现象的程序集.实验结果表明,本方法具有很好的检测效果.
여하유효지검측정서설계과정작업중적초습현상시일개중요적문제.전통적초습검측방법주요이용대마적속성혹결구신식래도량대마지간적상사성.급출료일충기우오차반향전파(BP산법)다층전향신경망락적대마초습검측방법.제취정서지간적7충비교특정작위신경망락적수입,경과망락계산후득출정서적상사치,병장해치여초습결책역치상비교이판정존재초습현상적정서집.실험결과표명,본방법구유흔호적검측효과.
It is very important to find plagiarized programs in the field of computer science education. Traditional methods for program similarity use attribute counting or structure information to detect plagiarism. This paper presented a program similarity detection approach based on back propagation (BP algorithm) multi-layer feed-forward neural networks. We extracted seven compared features of the code as the input of the neural network, and obtained the program similarity through the network calculation. Comparing the result with the threshold value, we can find all groups of similar programs. Experimental results show that our method is effective.