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

The component-based software system has a core that is based on architecture design. Predicting the reliability growth trends of a software system in the early stages of the development process is conducive to reducing waste and loss caused by blind development. Restricted by the lack of information...

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Bibliographic Details
Main Authors: Yuzhuo Wang, Haitao Liu, Haojie Yuan, Zhihua Zhang
Format: Article
Language:English
Published: PeerJ Inc. 2023-02-01
Series:PeerJ Computer Science
Subjects:
Online Access:https://peerj.com/articles/cs-1247.pdf
Description
Summary:The component-based software system has a core that is based on architecture design. Predicting the reliability growth trends of a software system in the early stages of the development process is conducive to reducing waste and loss caused by blind development. Restricted by the lack of information and data in the design and integration phase, it is difficult to implement reliability prediction research at this stage. In this article, we focus on a software system in which the reliability of each component follows the G-O model. First, two system-level parameters, which are the total number of system faults and the detection rate of the system faults, are defined. Then, by studying the relationship between the total number of faults and the detection rate of faults between the components and the system, the defined system parameters are calculated from the known component parameters. On this basis, and by incorporating the system parameters, we construct a reliability growth model for the software system, called the component-based generalized G-O model (CB-GGOM). Besides, two approximate models of CB-GGOM are proposed to facilitate reliability evaluation of the software system in the early and stable stages of the integration test. An engineering explanation of the proposed models is also provided, and their effectiveness is verified through simulation and with an authentic example. Since the proposed models are formulated without any integration test data, they are beneficial for developers to optimize test strategies of the software system and implement defect prevention in advance.
ISSN:2376-5992