An Improved Computational Software Reliability Model using ANFIS
|
10.5120/20060-2090 |
Shubhi Bhardwaj and Amit Sinha. Article: An Improved Computational Software Reliability Model using ANFIS. International Journal of Computer Applications 114(16):7-9, March 2015. Full text available. BibTeX
@article{key:article,
author = {Shubhi Bhardwaj and Amit Sinha},
title = {Article: An Improved Computational Software Reliability Model using ANFIS},
journal = {International Journal of Computer Applications},
year = {2015},
volume = {114},
number = {16},
pages = {7-9},
month = {March},
note = {Full text available}
}
Abstract
Software reliability is an important attribute of software engineering to ensure the success of software. Software reliability is the probability that there will no failure for a specified time. The reliability of the software depends on various attributes of software such as Size of software, Number of failures and Total time. These data sets of known software follow a specific trend which needs to be studied. The present work collects and analyzes these data sets. The training of these data sets is done through ANFIS. The relative error at definite epochs is noted. The software to be tested is then passed to same network that will give the desired result.
References
- Mohanthy, R. ; Naik, V. ; Mubeen, A. , "Software Reliability Prediction by Using Ant Colony Optimization Technique," Communication Systems and Network Technologies (CSNT), 2014 Fourth International Conference on , vol. , no. , pp. 496,500, 7-9 April 2014.
- Dongliang Yuan; Chenchen Zhang, "Evaluation strategy for software eliability based on ANFIS," electronics a communications and Control (ICECC), 2011 International Conference on , vol. , no. , pp. 3738,3741, 9-11 Sept. 2011
- https://sw. csiac. org/databases/sled/swrel. php
- Kun Han, Jun-Hai Cao, Shou-Hua Chen, Wei-Wei Liu" A Software Reliability Prediction Method Based on Software Development Process", 2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE).
- Khyati M. Mewada, Amit Sinhal and Bhupendra Verma" Adaptive Neuro-Fuzzy Inference System (ANFIS) Based Software Evaluation ",IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 5, No 1, September 2013. of Advanced Research in Computer Science and Software Engineering,Volume 2, Issue 10, October 2012
- Lawrence Bernstein, C. M. Yuhas, "Design Constraints That Make Software Trustworthy", IEEE-2008.
- D. Raheja, L. Gullo, "Developing reliable tools", IEEE-2012.
- Ivano Irrera, Joao Duraes, Marco Vieira," On the need for training Failure Prediction algorithms in evolving software systems" 2014 IEEE 15th International Symposium on High-Assurance Systems Engineering