{"title":"Method of Searching for Clones of the Program Code in Binary Executive Files","authors":"E. V. Zavadskii, A. V. Bulat, N. A. Gribkov","doi":"10.3103/S0146411624700913","DOIUrl":null,"url":null,"abstract":"<p>The modern trend of increasing labor productivity and business process efficiency entails the optimization of software development processes through the use of generative artificial intelligence models trained on various code bases and manual copying of code fragments. Given the growing number of registered vulnerabilities, methods for detecting clones of the software code are needed. A method for assessing the similarity of fragments of the program code of binary executable files, which is based on the representation of the code in the form of an FA-AAST tree and the apparatus of graph neural networks, is proposed. The results obtained during testing on open and closed source software demonstrate the correctness of the proposed method and higher accuracy compared to the solutions considered.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1263 - 1270"},"PeriodicalIF":0.6000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0146411624700913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The modern trend of increasing labor productivity and business process efficiency entails the optimization of software development processes through the use of generative artificial intelligence models trained on various code bases and manual copying of code fragments. Given the growing number of registered vulnerabilities, methods for detecting clones of the software code are needed. A method for assessing the similarity of fragments of the program code of binary executable files, which is based on the representation of the code in the form of an FA-AAST tree and the apparatus of graph neural networks, is proposed. The results obtained during testing on open and closed source software demonstrate the correctness of the proposed method and higher accuracy compared to the solutions considered.
期刊介绍：
Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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