Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning
Testing real-time embedded systems requires intelligent strategies that balance test coverage, timing constraints, and resource limitations. The traditional test case generation methods, such as random testing and conventional Q-learning, often fail to adapt to dynamic workloads and maintain real-ti...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Springer Nature Limited
2026
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/51519/1/s10515-026-00598-w.pdf http://ir.unimas.my/id/eprint/51519/ https://link.springer.com/article/10.1007/s10515-026-00598-w https://doi.org/10.1007/s10515-026-00598-w |
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