Software reliability modeling based on test coverage

In order to incorporate the effect of test coverage, two novel software reliability growth models (SRGMs) are proposed in this paper using failure data and test coverage simultaneously. One is continuous using testing time, and the other is discrete with respect to the number of executed test cases...

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Bibliographic Details
Published in:2011 9th International Conference on Reliability, Maintainability and Safety pp. 665 - 671
Main Authors: Shuanqi Wang, Yumei Wu, Minyan Lu, Haifeng Li
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2011
Subjects:
beta function
Equations
Fault detection
Mathematical model
mean value function
non-homogeneous poisson process
Software
Software reliability
Software reliability growth model
test coverage function
Testing
ISBN:9781612846675, 161284667X
Online Access:Get full text
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Summary:In order to incorporate the effect of test coverage, two novel software reliability growth models (SRGMs) are proposed in this paper using failure data and test coverage simultaneously. One is continuous using testing time, and the other is discrete with respect to the number of executed test cases instead of testing time. Since one of the most important factors of the coverage-based SRGMs is the test coverage function (TCF), we first discuss a discrete TCF based on Beta function. Then we develop mean value functions (MVF) of the two models integrating test coverage and imperfect debugging. Finally the proposed TCF and MVFs are evaluated and validated on actual software reliability data collected from real software development projects. The results demonstrate clearly that both the proposed TCF and SRGMs provide better estimation and fitting for the data sets under comparisons.
ISBN:9781612846675
161284667X
DOI:10.1109/ICRMS.2011.5979373