Presentation | 2003/9/12 Generalized-Gamma Software Reliability Model Hiroyuki OKAMURA, Mitsuaki ANDO, Tadashi DOHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, we consider a generalized software reliability model based on the non-homogeneous Poisson process (NHPP) under the assumption that the software fault detection time obeys a generalized-gamma distribution. The proposed model is regarded as a comprehensive model for several existing NHPP models, and is consistent to the probabilistic debugging theory based on the general order statistics concept. Further, we develop an efficient statistical estimation method for the model parameters based on the EM (Expectation-Maximization) algorithm and a heuristic approach. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | software reliablity model / NHPP / generalized-gamma distribution / EM algorithm / fault data analysis |
Paper # | SS2003-12 |
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Committee | SS |
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Conference Date | 2003/9/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Software Science (SS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Generalized-Gamma Software Reliability Model |
Sub Title (in English) | |
Keyword(1) | software reliablity model |
Keyword(2) | NHPP |
Keyword(3) | generalized-gamma distribution |
Keyword(4) | EM algorithm |
Keyword(5) | fault data analysis |
1st Author's Name | Hiroyuki OKAMURA |
1st Author's Affiliation | Department of Information Engineering, Graduate School of Engineering, Hiroshima University() |
2nd Author's Name | Mitsuaki ANDO |
2nd Author's Affiliation | Department of Information Engineering, Graduate School of Engineering, Hiroshima University |
3rd Author's Name | Tadashi DOHI |
3rd Author's Affiliation | Department of Information Engineering, Graduate School of Engineering, Hiroshima University |
Date | 2003/9/12 |
Paper # | SS2003-12 |
Volume (vol) | vol.103 |
Number (no) | 318 |
Page | pp.pp.- |
#Pages | 6 |
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