Bibliographische Detailangaben
| Titel: |
Sensitivity Analysis Considering Wiener Processes and Deep Learning for OSS Reliability Assessment. |
| Autoren: |
Okano, Seidai, Tamura, Yoshinobu, Yamada, Shigeru |
| Quelle: |
Journal of Graphic Era University; 2026, Vol. 14 Issue 1, p35-52, 18p |
| Schlagwörter: |
SENSITIVITY analysis, DEEP learning, OPEN source software, WIENER processes, DEFECT tracking (Computer software development) |
| Abstract: |
The demand of open source software is increasing because of the low cost, high quality, and short delivery. In particular, open source software is managed by using the bug tracking system. This paper focuses on the method of reliability assessment based on the deep learning. Then, theWiener process is applied to the output value of objective variables. Moreover, several sensitivity analyses of the parameter of Wiener process are shown as several numerical examples. [ABSTRACT FROM AUTHOR] |
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| Datenbank: |
Complementary Index |
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