Open AccessAnalyzing the Improved Software Reliability Based on the Markov Model by Considering Error propagation
Author(s) -
S. Srinivasa Rao,
D Sowjanya,
CH Dileep Chowdary,
M Harika
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.32.13534
Subject(s) - markov model , computer science , software quality , reliability (semiconductor) , markov chain , reliability engineering , transformation (genetics) , software , markov process , software reliability testing , model transformation , software development , machine learning , artificial intelligence , statistics , programming language , mathematics , engineering , power (physics) , physics , quantum mechanics , biochemistry , chemistry , consistency (knowledge bases) , gene
In the software reliability analysis we proposed an approach, which is named as Model Driven Development method. This is a modelling and model transformation techniques. The Markov model used in reliability elds is modied to adapt to error propagation behaviors of components. The Markov model has been used for results of reliability analysis. Markov model which means that that future or upcoming states depend only on the present state not on the events that occurred before it to ensure high reliability of this software is to estimate reliability accurately in the developing phase. Then a study on the transformation between model based on Architecture & Analysis Design Language (AADL) and Markov model has been done. By considering all these a model based software reliability analysis approach is proposed.