Neuro-Fuzzy Based Software Risk Estimation Tool

Pooja Rani; Dalwinder Singh Salaria

Neuro-Fuzzy Based Software Risk Estimation Tool

Pooja Rani * §

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Dalwinder Singh Salaria

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Lovely Professional University

Neuro-Fuzzy Based Software Risk Estimation Tool

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Abstract

To develop the secure software is one of the major concerns in the software industry. To make the easier task of finding and fixing the security flaws, software developers should integrate the security at all stages of Software Development Life Cycle (SDLC).In this paper, based on Neuro-Fuzzy approach software Risk Prediction tool is created. Firstly Fuzzy Inference system is created and then Neural Network based three different training algorithms: BR (Bayesian Regulation), BP (Back propagation) and LM (Levenberg-Marquardt) are used to train the neural network. From the results it is conclude that for the Software Risk Estimation, BR (Bayesian Regulation) performs better and also achieves the greater accuracy than other algorithms.

References

24 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Pooja Rani, Dalwinder Singh Salaria. 2013. "Neuro-Fuzzy Based Software Risk Estimation Tool". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C6).

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GJCST Volume 13 Issue C6

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Fuzzy logic Neural Network neuro-fuzzy Software Security software threat

Classification

GJCST-C Classification D.2.9

Submission ReceivedDecember 11, 2012
Peer Review Double Blind
Handling Editor
Accepted December 31, 2012
Published January 15, 2013

Version of record

v1.2

Issue date

June 4, 2013

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Pooja Rani, Dalwinder Singh Salaria (PhD/Dr. count: 0)

View Count (all-time): 401

Total Views (Real + Logic): 2190

Total Downloads (simulated): 99

Publish Date: 2013 01, Tue

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Total Views: 2.2K

Total Downloads: 99

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