Fast similarity detection and evidence generation for large-scale programs based on code mapping and lexical analysis

Abstract

The invention discloses a fast similarity detection and evidence generation for large-scale programs based on code mapping and lexical analysis. Two-layer similarity detection method is used to detectplagiarism and generate evidence for large-scale software samples. Firstly, the code mapping method is used to analyze the coarse-grained similarity of large-scale programs and search for suspected similar programs quickly. Lexical analysis is then used to fine-grained analyze suspicious similar programs, determine program similarity and generate similar code evidence. Through the above methods,we can quickly and accurately find the plagiarized code in large-scale samples, and provide corresponding evidence to support it.

Description

technical field [0001] The invention relates to the technical field of source code program analysis and software plagiarism detection, in particular to a multi-layer source code program similarity detection method. Background technique [0002] With the rapid development of the computer software industry, more and more researchers, educators and software companies pay more and more attention to the security of software. The open source of computer software has brought more convenient conditions for software plagiarism. In recent years, various software infringement cases have occurred from time to time, and Google, Apple, eBay, etc. have all been involved in related cases. [0003] In order to combat software plagiarism cases and protect software intellectual property rights, researchers at home and abroad have proposed a large number of software plagiarism detection technologies. Based on application scenarios and technical means, existing software plagiarism detection te...

AI Technical Summary

Problems solved by technology

[0005] 1) At present, most source code detection technologies are oriented to small-scale plagiarism detection, which cannot meet the needs of rapid detection in large-scale plagiarism detection scenarios;

[0006] 2) The development of obfuscation technology increases the difficulty of software plagiarism detection, which will make some plagiarism detection technologies invalid;

[0007] 3) Many existing plagiarism detection technologies only provide a simple result, and do not provide specific and strong evidence of plagiarism;

[0008] 4) Existing plagiarism detection technology is difficult to achieve simultaneous optimization of detection accuracy and time overhead, and many plagiarism detection methods cannot be put into application

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