• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1915-1925
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• 1998

The switching system software is large scale, real-time multi-task system which requires high reliability. The reliability assessment of large-scale software is very important for the success of software development project. For this raeson, the software quality measurement is much more important. In this paper, we have learned about the software reliability, metho of the analysis of failure data and estimation of software quality. To estimate the software reliability, using the failure data found during of the system test. We apply the two software reliability growth models, named Goel-Okumoto(G-O) and S-shaped model, to estimate the software reliability. Also, we compared with the results and we reviewed fully not only development cycle but validation and verification of the test data, for each software versions. This paper presents a software reliability model that suitale the software development project and the activeity of quality control for the switching system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4A
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• pp.399-414
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• 2004

In this paper, an evolution of software reliability engineering in a large-scale software project is summarized. The considered software consists of many components, called functional blocks in software of switching system. These functional blocks are served as the unit of coding and test, and the software is continuously updated by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components in software reliability and reliability evolution. We analyze the static characteristics of the software related to software reliability using collected failure data during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of system software, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto(G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources fur a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.