Software reliability analysis considering the fault detection trends for big data on cloud computing

Abstract

Recently, the cloud computing with big data is known as a nextgeneration software service paradigm. However, the effective method of software reliability assessment considering the big data and cloud computing has been only few presented. In particular, the big data on cloud computing is managed by using several software, i.e., Hadoop and NoSQL are used as the bigdata- targeted processing software, OpenStack and Eucalyptus are well-known as the cloud computing software. In this paper, we propose the method of component- based reliability assessment for the software such as database and cloud. Moreover, we propose the method of system-wide reliability assessment considering the big data on cloud computing. In particular, we deeply analyze the software reliability based on two kinds of data set in terms of the background factors. Then, we analyze the software failure-occurrence time data and the cumulative number of detected faults data by applying the hazard rate model and stochastic differential equation one. Additionally, we show several numerical examples for the actual data.