Concurrent access to shared data may result in data inconsistency.

Here's why:

1. When multiple processes access the same data concurrently, there's a chance they might try to modify it at the same time.

2. If Process A reads data, then Process B reads the same data and modifies it, Process A may be working with outdated information if it tries to modify the data later.

3. This can lead to a state where different processes have different views of the data, or where the final state of the data depends on the order of operations, which is generally not predictable in a concurrent system.

4. This situation is known as a race condition and it's one of the main sources of data inconsistency in concurrent systems.

5. Therefore, mechanisms like locks, semaphores, or transactions are used in concurrent programming and databases to prevent these issues and ensure data consistency.

Question

Concurrent access to shared data may result in data inconsistency.

Here's why:

1. When multiple processes access the same data concurrently, there's a chance they might try to modify it at the same time.

2. If Process A reads data, then Process B reads the same data and modifies it, Process A may be working with outdated information if it tries to modify the data later.

3. This can lead to a state where different processes have different views of the data, or where the final state of the data depends on the order of operations, which is generally not predictable in a concurrent system.

4. This situation is known as a race condition and it's one of the main sources of data inconsistency in concurrent systems.

5. Therefore, mechanisms like locks, semaphores, or transactions are used in concurrent programming and databases to prevent these issues and ensure data consistency.

Knowee AI · Accepted Answer

Concurrent access to shared data may result in data inconsistency.

Here's why:

1. When multiple processes access the same data concurrently, there's a chance they might try to modify it at the same time.

2. If Process A reads data, then Process B reads the same data and modifies it, Process A may be working with outdated information if it tries to modify the data later.

3. This can lead to a state where different processes have different views of the data, or where the final state of the data depends on the order of operations, which is generally not predictable in a concurrent system.

4. This situation is known as a race condition and it's one of the main sources of data inconsistency in concurrent systems.

5. Therefore, mechanisms like locks, semaphores, or transactions are used in concurrent programming and databases to prevent these issues and ensure data consistency.

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Concurrent access to shared data may result in

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