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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| Published in: | 2011 9th International Conference on Reliability, Maintainability and Safety pp. 665 - 671 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.06.2011
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| Subjects: | |
| ISBN: | 9781612846675, 161284667X |
| Online Access: | Get full text |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Yumei Wu Shuanqi Wang Haifeng Li Minyan Lu |
| Author_xml | – sequence: 1 surname: Shuanqi Wang fullname: Shuanqi Wang email: wangshuanqi@163.com organization: Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China – sequence: 2 surname: Yumei Wu fullname: Yumei Wu email: wuyumei@buaa.edu.cn organization: Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China – sequence: 3 surname: Minyan Lu fullname: Minyan Lu email: lmy@buaa.edu.cn organization: Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China – sequence: 4 surname: Haifeng Li fullname: Haifeng Li email: lihaifeng@dse.buaa.edu.cn organization: Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China |
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| Snippet | 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... |
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| SubjectTerms | 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 |
| Title | Software reliability modeling based on test coverage |
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