Analyzing source codes and detecting similarities

Plagiarism in academic institutions is often expressed as copying someone else's work (i.e., another students or from sources such as books). By reason of the fact that innovations and developments are occurred in technology of late years, massive increase of software applications is monitored. Concordantly, plagiarism issue becomes more significant day by day. Plagiarism of programming source codes is an undesirable situation in the many fields of software development world. Especially in educational field, it is obviously realized that plagiarism in programming courses increases consistently. The aim of this study is attempting to answer questions such as "which codes are similar?", "what similarity ratios are?" in order to prevent plagiarism among collage students who attend programming courses. There are many methods and tools are available to find similarities between program codes. Generally traditional methods are preferable while detecting similarities among source codes. One of these traditional methods is finding metrics in software documents. However, different approaches are seen in recent years while solving plagiarisim problems. N-gram method that belongs Natural Language Process (NLP) can be given as example of different approaches. While developing the proposed methodology, metric extraction method (fingerprint system), N-gram algortihm and Vector Space Model (VSM) were considered. Information Retrieval (IR) System and Cosine Normalization (CN) methods were utilized to calculate similarity ratios. Experimental study was performed on datasets of two different kinds. First type was created by collecting assignments of students who attend programming courses in Software Engineering Department of Celal Bayar University. Second type is yielded by changing source code examples in different forms. The results obtained provide convincing evidence that the study is fit the purpose.The experimental results about proposed methods give success when compared with the previous methods.