Software Reliability Growth Model for N-Version Fault Tolerant Software with Common and Independent Faults

Research and development teams have become increasingly focused on developing highly reliable software for safety-critical systems. It is a major challenge for real-time control systems to achieve high reliability software to meet safety standards. A reliability evaluation focuses primarily on analytical and modeling techniques for fault prediction. In safety-critical systems like nuclear plant controls, aircraft controls and railroad signalization systems, N-version programming (NVP) is an effective technique for raising software's reliability, particularly in areas with high-risk ratios because small errors can result in hazardous incidents. It allows the software to be fault-tolerant, aiding it to produce accurate results even when the software has faults. We present an analytical method for assessing the reliability of N-version software systems. Analysis of the system's reliability and other performance metrics is provided with closed-form expressions. As an additional extension, we conduct numerical analyses of two cases, the 2VP system and 3VP system, in which suitable parameters are used. We conduct numerical simulations using MATLAB to generate the analytical results and compare the analytical results by using numerical results and neuro-fuzzy results using fuzzy interference systems.