A Markov Error Propagation Model for Component-based Software Systems

Abstract

In this paper, we propose a Markov chain-based error propagation model to analyze the reliability of component-based software systems and take measures to make the critical components safer. Because it is difficult to test the whole component-based system, we apply an error propagation model to evaluate the reliability of the system with parameters obtained by preliminary data from existing components and integration testing from two connected components. The main parameters required in our Markov model are the error probability for each component, the error tolerance probability, and the error propagation probability for every two connected components. Our model is applied to compute the reliability of the system, find the most suspicious component during debugging, and protect the critical components. Finally, we simulate the process of these three applications using three different systems on MATLAB.

Understanding the Reliability of the Complex System Having Two Standby Units: A Transdisciplinary Approach

“…Their total performance is reduced as a result of this steady that include production efficiency, availability, and reliability and explained how to predict these performance indicators. A Markov chain-based error propagation model was presented by Tian et al [11] to assess component-based software systems' reliability and protect their vital components. Ren and Guo [12] described a technique for computing dependability that incorporates an error propagation model based on Markov chains.…”