An Efficient Source Code Auditing using Fuzzy Decision Tree
Author(s) -
Rani Sahu,
Shailendra Kumar
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016912549
Subject(s) - computer science , audit , decision tree , fuzzy logic , code (set theory) , tree (set theory) , source code , data mining , data science , artificial intelligence , accounting , programming language , business , mathematics , mathematical analysis , set (abstract data type)
Here in this paper the discovery of Vulnerabilities in the Source Codes is proposed. The Proposed Methodology applied is based on the Concept of Fuzzy Based Decision Tree. The Methodology adopted here for the Checking of Codes Vulnerabilities provides efficient discovery of Vulnerabilities and hence provides improved performance and high precision and Recall. The Proposed Methodology Audits the source code and searches the possible vulnerabilities on the basis of Rules generated Fuzzy Decision Tree. Various Experimental results are achieved on numerous datasets and shows that the proposed methodology provides better accuracy in comparison.
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