Development of Software Reliability Growth Models for Industrial Applications Using Fuzzy Logic | Science Publications

Journal of Computer Science

Sultan Aljahdali¹ 

关键词: Software Reliability Growth Models (SRGM);    Takagi-Sugeno technique;    Fuzzy Logic (FL);    Artificial Neural Net-works (ANN);    Genetic Programming (GP);    model structure;    linear regression model;    NASA space;   

DOI  :  10.3844/jcssp.2011.1574.1580

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: The utilization of Software Reliability Growth Models (SRGM) plays a major role in monitoring progress, accurately predicting the number of faults in the software during both development and testing processes; define the release date of a software product, helps in allocating resources and estimating the cost for software maintenance. This leads to achieving the required reliability level of a software product. Approach: We investigated the use of fuzzy logic on building SRGM to estimate the expected software faults during testing process. Results: The proposed fuzzy model consists of a collection of linear sub-models, based on the Takagi-Sugeno technique and attached efficiently using fuzzy membership functions to represent the expected software faults as a function of historical measured faults. A data set provided by John Musa of bell telephone laboratories (i.e., real time control, military and operating system applications) was used to show the potential of using fuzzy logic in solving the software reliability modeling problem. Conclusion: The developed models provided high performance modeling capabilities.

【 授权许可】

Unknown