• DocumentCode
    1945358
  • Title

    Disputed Authorship in C Program Code after Detection of Plagiarism

  • Author

    Zhao, Jie ; Zhan, Guohua ; Feng, Juan

  • Author_Institution
    Inf. Sci. & Eng. Sch., Hang Zhou Normal Univ., Hangzhou
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    86
  • Lastpage
    89
  • Abstract
    In recent years disputed authorship in source code has been congruently neglected after detection of plagiarism has been heatedly debated for a long period, theoretical and feasible measures have been taken to weight its property. In this paper, according to existence of individual but distinct programming style, the authors, with aid of SVM (support vector machine), one tool of neural networks and a series of algorithm, examine a brand-new application to puzzle out who is the real writer in C programming surrounded by crowds of reputed ones . The whole algorithm in SVM is a process to carry out: first, refined the frequencies as training sets through math formulas such like Gauss axiom, Lagrange formula are classified into value 1 or -1; then travel neural networks to get result sequence .it is a feasible approach to detect the authorship in C programming after detection of plagiarism.
  • Keywords
    C language; copy protection; neural nets; support vector machines; C program code; C programming; Gauss axiom; Lagrange formula; disputed authorship; neural networks; plagiarism detection; source code; support vector machine; Educational institutions; Gaussian processes; Information science; Lagrangian functions; Neural networks; Plagiarism; Standards development; Standards publication; Support vector machine classification; Support vector machines; Gauss Axiom; Neural Networks; SVM; entropy; programming style; saddle of Lagrange formula;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.620
  • Filename
    4721698