In Java multithreading, what is synchronization and why is it important when multiple threads access shared data?

Introduction / Context:
Modern Java applications frequently use multiple threads to improve performance, responsiveness, and scalability. However, when threads share data, careless access can lead to inconsistent state, corrupted structures, and hard to reproduce bugs. Synchronization is the technique Java provides to control how threads interact with shared resources. Interviewers often ask about synchronization to check your understanding of thread safety and concurrent programming fundamentals.

Given Data / Assumptions:

• Multiple Java threads may execute code that reads and writes the same fields or data structures.
• Without coordination, thread scheduling by the JVM and operating system is unpredictable.
• Critical sections of code require exclusive access to maintain consistent state.
• Java provides synchronized blocks, synchronized methods, and monitor locks associated with objects.

Concept / Approach:
Synchronization in Java is about coordinating threads so that only one thread at a time executes a block of code that manipulates shared mutable data. This is achieved by acquiring and releasing intrinsic locks, also called monitors, associated with objects or classes. When a thread enters a synchronized method or block, it acquires the corresponding lock; other threads attempting to enter synchronized code guarded by the same lock must wait until the lock is released. This mutual exclusion prevents race conditions where threads interleave operations in ways that produce incorrect or inconsistent results. Synchronization also establishes happens before relationships that guarantee visibility of changes between threads.

Step-by-Step Solution:
Step 1: Identify shared mutable data, such as a counter, list, or map that is accessed by multiple threads. Step 2: Determine which operations on this data must be atomic, such as increment and read, or add and iterate. Step 3: Wrap these critical sections in synchronized methods or synchronized blocks that lock on a chosen monitor object. Step 4: When a thread enters the synchronized region, it acquires the lock, executes the critical code, and then releases the lock on exit. Step 5: Other threads attempting to enter the same synchronized region will block until the lock becomes available, ensuring safe, ordered access to the shared data.

Verification / Alternative check:
You can verify the importance of synchronization by writing a simple program that increments a shared counter from many threads without using synchronized and observing inconsistent results, such as a final count lower than expected. Adding proper synchronized blocks around the increment restores correct behavior. Tools and libraries such as java.util.concurrent provide higher level abstractions, but they are built on the same fundamental need to control thread access to shared state and to ensure memory visibility across threads.

Why Other Options Are Wrong:
Option B is incorrect because synchronization does not automatically parallelize single threaded code; it simply coordinates access in already multithreaded applications. Option C is wrong because formatting strings is unrelated to synchronization and thread safety. Option D is clearly incorrect since backing up data is an operational task, not a concurrency control mechanism built into the Java language.

Common Pitfalls:
Common pitfalls include using too coarse a lock, which can reduce throughput by serializing too much work, or too fine grained locks, which can introduce deadlocks. Another mistake is relying only on synchronized for coordination without considering higher level constructs like ReentrantLock, ReadWriteLock, or thread safe collections. Developers must also remember that synchronization affects both mutual exclusion and memory visibility; omitting it can lead to stale reads even when race conditions seem unlikely.

Final Answer:
Synchronization in Java is the coordination of multiple threads using locks so that only one thread at a time executes critical sections that access shared data, thereby preventing race conditions and keeping program state consistent.