Is a Kotlin Object Thread-Safe Without Extra Synchronization?

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Kotlin provides a powerful object declaration that simplifies singleton creation. But an important question arises: Is a Kotlin object completely thread-safe without additional synchronization? The answer is nuanced. While the initialization of an object is thread-safe, the state inside the object may not be. This post dives deep into Kotlin object thread safety, potential pitfalls, and how to make objects fully safe for concurrent access.

Why Are Kotlin Objects Considered Thread-Safe?

Kotlin object declarations follow the JVM class loading mechanism, which ensures that an object is initialized only once, even in a multi-threaded environment. This guarantees that the creation of the object itself is always thread-safe.

Kotlin
object Singleton {
    val someValue = 42  // Immutable, safe to access from multiple threads
}
  • Here, Singleton is initialized only once.
  • The property someValue is immutable, making it inherently thread-safe.

If all properties inside the object are immutable (val), you don’t need to worry about thread safety.

When Is a Kotlin Object NOT Thread-Safe?

Although the initialization of the object is safe, modifying mutable state inside the object is NOT automatically thread-safe. This is because multiple threads can access and modify the state at the same time, leading to race conditions.

Kotlin
import kotlin.concurrent.thread

object Counter {
    var count = 0  // Mutable state, not thread-safe

    fun increment() {
        count++  // Not atomic, can lead to race conditions
    }
}

fun main() {
    val threads = List(100) {
        thread {
            repeat(1000) {
                Counter.increment()
            }
        }
    }
    threads.forEach { it.join() }
    println("Final count: ${Counter.count}")
}

What’s wrong here?

  • count++ is not an atomic operation.
  • If multiple threads call increment() simultaneously, they might overwrite each other’s updates, leading to incorrect results.

How to Make a Kotlin Object Fully Thread-Safe?

Solution 1: Using synchronized Keyword

One way to make the object thread-safe is by synchronizing access to mutable state using @Synchronized.

Kotlin
object Counter {
    private var count = 0

    @Synchronized
    fun increment() {
        count++
    }

    @Synchronized
    fun getCount(): Int = count
}

Thread-safe: Only one thread can modify count at a time. 

Performance overhead: synchronized introduces blocking, which might slow down performance under high concurrency.

Solution 2: Using AtomicInteger (Better Performance)

A more efficient alternative is using AtomicInteger, which provides lock-free thread safety.

Kotlin
import java.util.concurrent.atomic.AtomicInteger

object Counter {
    private val count = AtomicInteger(0)

    fun increment() {
        count.incrementAndGet()
    }

    fun getCount(): Int = count.get()
}

Thread-safe: AtomicInteger handles atomic updates internally. 

Better performance: Avoids blocking, making it more efficient under high concurrency.

Solution 3: Using ConcurrentHashMap or ConcurrentLinkedQueue (For Collections)

If your object manages a collection, use thread-safe collections from java.util.concurrent.

Kotlin
import java.util.concurrent.ConcurrentHashMap

object SafeStorage {
    private val data = ConcurrentHashMap<String, String>()

    fun put(key: String, value: String) {
        data[key] = value
    }

    fun get(key: String): String? = data[key]
}

Thread-safe: Uses a concurrent data structure. 

No need for explicit synchronization.

Conclusion

A Kotlin object is always initialized in a thread-safe manner due to JVM class loading mechanisms. However, mutable state inside the object is NOT automatically thread-safe

To ensure full thread safety:

  • Use @Synchronized for simple synchronization.
  • Use AtomicInteger for atomic operations.
  • Use ConcurrentHashMap or ConcurrentLinkedQueue for collections. 

For optimal performance, prefer lock-free solutions like atomic variables or concurrent collections.

By understanding these nuances, you can confidently write thread-safe Kotlin objects that perform well in multi-threaded environments.

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