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[ Option D ]

ACID is a set of properties that ensure reliable processing of database transactions:

[ Option D ]

In the given schedule, we have the following operations, T1 writes Q before T2 reads Q, T2 reads Q before T3 writes Q, and T3 writes Q before T4 writes Q. These create directed edges T1 → T2, T2 → T3, and T3 → T4 in the precedence graph. Since this graph has no cycles (acyclic), the schedule is conflict serializable and equivalent to the serial order T1 → T2 → T3 → T4.

[ Option B ]

The number of uncommitted transactions is the smallest, the UNDO mechanism requires the recovery manager to attend to the least number of transactions.

[ Option A ]

The ACID properties define the key characteristics that ensure reliable database transactions. ACID stands for Atomicity, Consistency, Isolation, and Durability.

[ Option C ]

Atomicity refers to the concept where a sequence of operations is executed as a single indivisible unit. This means either all operations are completed successfully or none are executed at all.
It is an important property in Transactions and Concurrent systems, ensuring consistency and preventing partial execution.

[ Option B ]

Atomicity ensures that a transaction is treated as a single, indivisible unit. This means either all operations of the transaction are performed, or none of them are applied if a failure occurs.
For example, during a fund transfer, if money is debited from one account but crediting fails, atomicity ensures the debit is rolled back.

[ Option A ]

Deadlock prevention schemes in databases use timestamp ordering to avoid cyclic waiting. Two popular timestamp-based methods are wait-die and wound-wait schemes.

In the wait-die scheme (non-preemptive), if an older transaction requests a resource held by a younger one, it is allowed to wait, otherwise, the younger transaction is rolled back.

The wound-wait scheme (preemptive) allows the older transaction to “wound” the younger one by forcing it to roll back immediately and release the resource. Because wait-die involves waiting (non-preemptive) and wound-wait involves forced rollback (preemptive).

[ Option A ]

The data item Q initially = 500.
Schedule Step by Step:

• T1: Read(Q) : Reads Value 500
• T2: Read(Q) : Also Reads Value 500
• T1: Q = Q + 100 : T1 computes 600 (Local T1 Value)
• T2: Q = Q + 100 : T2 computes 600 (Based on old Value 500 and Local T2 Value)
• T2: Write(Q) : T2 writes 600 to the database.
• T1: Write(Q) : T1 then writes 600 to the database, which overwrites T1 write.

Because both transactions read the original value 500 and each computed 600, the second write simply overwrites the first with the same value. The final value of Q after the last operation is 600.

[ Option D ]

A transaction in DBMS is a logical unit of work that ends when its changes are either made permanent or undone, or when it is implicitly terminated.

• COMMIT or ROLLBACK explicitly ends a transaction by saving or undoing changes.
• Executing a DDL or DCL statement such as CREATE, ALTER, GRANT causes an implicit commit, which ends the current transaction.
• If a user exits or the session ends unexpectedly, the database implicitly performs a ROLLBACK, ending the transaction.

[ Option A ]

The schedule S: w1(A); w1(B); w2(A); r2(B); c2; c1; involves two transactions T1 and T2. Checking for Recoverability, T2 reads data written by T1 and commits before T1 commits, which violates recoverable schedule rules. Hence, the schedule is Not Recoverable.

For Serializability, analyzing conflicting operations shows that T1’s writes on A and B conflict with T2’s operations, resulting in a precedence graph with a single edge from T1 to T2. Since the graph is acyclic, the schedule is conflict serializable. Therefore, the schedule is serializable but not recoverable.

[ Option C ]

Shadow Paging keeps a copy of the old page table and replaces it at commit, which makes it incompatible with multiple concurrent transactions because changes cannot be merged safely. 
On the other hand, Log-Based Techniques maintain a log of all changes and can safely support multiple concurrent transactions, providing both undo and redo capabilities during recovery.

[ Option D ]

Both transactions run under REPEATABLE READ isolation level using a standard locking mechanism. When a transaction reads a row, it acquires a shared lock, and when it writes to a row, it upgrades to an exclusive lock. If two transactions try to lock resources in different orders, a deadlock may occur.
Here, T1 reads A then B, while T2 reads B then A. This opposite order can cause deadlock, so options (b) and (c) are possible because the system may resolve the deadlock by rolling back either transaction. 
It is also possible that transactions execute sequentially or one waits for the other, resulting in the net transfer cancelling out, leaving both balances Rs. 5,000, making option (a) possible.
However, the state A = 4,000 and B = 6,000 would occur only if T1 completes without the effect of T2 being applied, which contradicts the assumption that both transactions are executed and controlled by locking under the REPEATABLE READ isolation level. Therefore, this situation will never occur.