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An Efficient Source Code Auditing using Fuzzy Decision Tree

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Rani Sahu, Shailendra Kumar Shrivastava

Rani Sahu and Shailendra Kumar Shrivastava. An Efficient Source Code Auditing using Fuzzy Decision Tree. International Journal of Computer Applications 156(14):19-22, December 2016. BibTeX

	author = {Rani Sahu and Shailendra Kumar Shrivastava},
	title = {An Efficient Source Code Auditing using Fuzzy Decision Tree},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {14},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {19-22},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2016912549},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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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Software, Auditing, Fuzzing, Vulnerabilities, Fault Prediction, Vulnerabilities Prediction