The Robust Architecture Based Reliability Analysis Framework of Complex Software System Using In-Degree and Out-Degree

Abstract

Nowadays, Software development process has incorporated many techniques, scientific approaches and advanced tools to develop the highest quality featured software. The size of the software systems also become large and make the system more complex. So that, it is necessary to ensure the quality of software system before its delivery. Software reliability is one of the important measurement to predict the quality of software which will be used to reduce the time, cost and other resources required for the testing process. Here we have proposed one novel framework to predict the software reliability based on software architecture and path testing by incorporating indegree and out-degree concept used in graph theory. This proposed framework will reduce the number of test path in the system which will be used to reduce the testing time and resources. The applicability of our proposed framework is validated by using two real time case studies and these results are compared with the prevailing standard reliability models to assess the prediction accuracy of our proposed framework. The result shows that our proposed framework is simple to apply in the real time system and prediction accuracy is also acceptable compared to the other models.

Comprehensive evaluation of software system reliability based on component-based generalized G-O models

“…To shorten the reliability evaluation time, Shanmugaiah & Ayyaswamy (2019) proposed a system reliability prediction framework based on the graph theory. This framework did not exhaust all test paths, so it saved test time while ensuring evaluation accuracy.…”

Evaluating the importance of nodes in the urban logistics UAV distribution network based on complex network theory

“…The incoming degree is the number of edges pointing to a site directly connected with the site, and the outgoing degree is the number of edges pointing from a site to the site directly connected to it. Therefore, the degree of a node is divided into total degree, in-degree, and out-degree, which are respectively denoted as k total (i), k in (i), k out (i) [6] :…”

“…However, identifying sites with high importance in the urban logistics UAV distribution networks is a crucial issue in developing this field [1][2][3] . Complex network analysis is a widely-used tool for abstract analysis of complex network problems, and evaluation methods for key nodes in complex networks are increasingly based on comprehensive considerations [4][5][6] . Lin et al [1] conducted research on the application method of swarm UAVs using complex networks.…”