Reliability assessment of CubeSat nanosatellites flight software by high-order Markov chains

In complex software, such as various intelligent monitoring and control systems, the requirements for its reliability and safety increase. However, traditional reliability models cannot longer describe its reliability behavior with sufficient accuracy. This paper presents an approach to software reliability assessment using high-order Markov chains on an example of CubeSat nanosatellites flight software. The method uses the developed algorithm of high-order Markov process representation through an equivalent first-order process. The simulation results show that high-order Markov chains can increase the accuracy of the failure rate assessment up to 50%. Hence, the usage of the high-order reliability models is obvious for accurate and reliable evaluation of software reliability and safety. (c) 2021 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the KES International.

Automated summary

This paper presents an approach to software reliability assessment using high-order Markov chains on an example of CubeSat nanosatellites flight software. The simulation results show that high-order Markov chains can increase the accuracy of the failure rate assessment up to 50%. The usage of high-order reliability models is essential for accurate and reliable evaluation of software reliability and safety.