A Fuzzy Neural Network Approach for Assessment and Enhancing Software Reliability

A Fuzzy Neural Network Approach for Assessment and Enhancing Software Reliability

Theyyagura M.K. Reddy Madhwaraj Kango Gopal

Research Scholar, Department of IT, VFSTR Deemed to be University, Vadlamudi, Guntur, India

Professor, Department of IT, VFSTR Deemed to be University, Vadlamudi, Guntur, India

Corresponding Author Email: 
manikantareddy.t@gmail.com, drkgm_it@vignanuniversity.org
Page: 
539-550
|
DOI: 
https://doi.org/10.18280/ama_b.600302
Received: 
26 December 2017
|
Accepted: 
3 January 2018
|
Published: 
31 September 2017
| Citation

OPEN ACCESS

Abstract: 

Software Reliability is the probability of non-failure software procedure for a predefined duration in a predetermined domain. Software Reliability is similarly an imperative factor manipulating structure with reliability [2]. It contrasts from hardware reliability in the way that it reflects the outline faultlessness, and to provide reliable software. The elevated intricacy of software is the major contributing element of Software Reliability issues. Software reliability engineering (SRE) surveys how well software based items and administrations meet client's operational needs. SRE utilizes quantitative techniques in view of reliability measures to do this evaluation. The essential objective of SRE is to boost consumer loyalty. SRE uses such quantitative strategies as factual estimation and expectation, estimation, and displaying. As the reliability of an item or administration is profoundly subject to working conditions and the reliability of software is identified with how the product is utilized, the quantitative portrayal of the utilization of software is an indispensable part in SRE. Software Cost Estimation with resonating unwavering quality, profitability and improvement exertion is a testing and burdensome undertaking. This has prompted the product group to give much required push and dig into broad research in Software exertion estimation for developing refined strategies. Estimation by similarity is one of the practical strategies in Software exertion estimation field. Be that as it may, the technique used for the estimation of Software exertion by similarity can't deal with the all-out information in an express and exact way. Another approach has been created in this paper to assess Software exertion for ventures spoke to by all out or numerical information utilizing thinking by similarity and fluffy approach. The current chronicled datasets, investigated with fluffy rationale, deliver precise brings about correlation with the dataset examined with the before approaches. Software designing is a more extensive training of which SRE is a sub train. Software building is worried about all parts of outlining, executing, and dealing with the advancement of software [8]. Different parts of software building incorporate the financial aspects of creating software and the interfaces between software, frameworks, and people and with the practices and procedures for guaranteeing the nature of conveyed software. In this paper we ponder the product reliability of frameworks with the assistance of past failure related informational collections by utilizing Fuzzy Neural Networks (FNN) methods, Numerical cases are appeared with both real and mimicked datasets. Better execution of software reliability evaluation is watched, contrasted and unique FNN demonstrate with no such verifiable failure related information joined.

Keywords: 

Software reliability, Quality evaluation, Software failure, Fuzzy-neural approach, Software reliability engineering.

1. Introduction
2. Related Data
3. Software Failure Mechanisms
4. Classification of Software Reliability Methods
5. Experiment Results
6. Conclusion
  References

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