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Safety-critical systems not only use mechanisms to reduce the occurrence of state inconsistency, but also require methods to recover from state inconsistency for safety.
A state inconsistency handler contains the method for detecting state inconsistency and the method of rolling back to the immediate checkpoint.
This faulty decision causes state inconsistency among the stations in the system.
To resolve the remaining state inconsistency, we generate fault-tolerant schedules using the optimization solver.
A detection scheme first identifies the occurrence of a state inconsistency.
A recovery scheme resolves the state inconsistency upon detecting it by running recover algorithms.
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Since the global replay bound is ten, the system can tolerate these ten state inconsistencies.
Therefore, the system can handle ten repeated state inconsistencies at any slot in a cycle.
The more the number of inconsistency handlers in between checkpoints, the more the system can tolerate state inconsistencies.
The paper deals with state inconsistencies which can occur in schedules that have the capability of conditional executions.
The other way to handle repeated state inconsistencies is to set a replay bound at the data slots.
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