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<article article-type="research-article" dtd-version="1.3" xml:lang="en">
  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-id journal-id-type="elibrary">9004</journal-id>
      <journal-title-group>
        <journal-title>Problems of information security. Computer systems</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Проблемы информационной безопасности. Компьютерные системы</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2071-8217</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">7</article-id>
      <article-id pub-id-type="doi">10.48612/jisp/gnad-nf3e-63te</article-id>
      <title-group>
        <article-title>Detecting source code fragments similarity with machine learning algorithms</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Определение схожести фрагментов исходных программных кодов с использованием методов машинного обучения</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Gribkov</surname>
            <given-names>Nikita</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>gribkov.na@edu.spbstu.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-2009-5460</contrib-id>
          <name>
            <surname>Ovasapyan</surname>
            <given-names>Tigran</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>otd@ibks.spbstu.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Moskvin</surname>
            <given-names>Dmitry</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>moskvin_da@spbstu.ru</email>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St. Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2023-03-19">
        <day>19</day>
        <month>03</month>
        <year>2023</year>
      </pub-date>
      <issue>1</issue>
      <fpage>62</fpage>
      <lpage>71</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://jisp.spbstu.ru/userfiles/files/2023_1.pdf"/>
      <abstract xml:lang="en">
        <p>The paper proposes a method for detecting source code fragments similarity using attribute abstract syntax trees and machine learning algorithms. The advantages of the method are determined based on a comparative analysis of existing approaches of detecting code clones. For
approaches, which use AST, it is possible to increase the efficiency of detecting similar source code fragments by detecting semantic clones with usage of method proposed.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>code clones</kwd>
        <kwd>syntactic similarity</kwd>
        <kwd>semantic similarity</kwd>
        <kwd>open-source software</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
