Aprenda Limitations of Threads | Concurrency Basics in Kotlin

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When you work with concurrency in Kotlin, using threads directly might seem straightforward at first, but several key limitations quickly become apparent. Here are the main drawbacks you will encounter:

High resource usage: Each thread consumes a significant amount of memory and system resources, which can lead to performance degradation if too many threads are created;
Increased complexity: Managing thread lifecycles, synchronization, and communication between threads adds substantial complexity to your code;
Error-proneness: It is easy to introduce subtle bugs such as race conditions, deadlocks, or resource leaks when dealing with low-level thread management.

These issues make it challenging to build scalable, maintainable, and reliable concurrent applications using only threads.

Main.kt


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package com.example

fun main() {
    val sharedCounter = Counter()

    val threads = List(100) { index ->
        Thread {
            repeat(1000) {
                sharedCounter.increment()
            }
            if (index == 0) {
                println("Thread 0 finished")
            }
        }
    }

    threads.forEach { it.start() }
    threads.forEach { it.join() }

    println("Final counter value: ${sharedCounter.value}")
}

class Counter {
    var value = 0

    fun increment() {
        value++ // Not thread-safe: potential race condition
    }
}

In the example above, you create 100 threads, each incrementing a shared counter 1,000 times. This approach highlights several problems. First, creating a large number of threads can exhaust system resources, leading to sluggish performance or even application crashes. Second, the increment function is not thread-safe, so multiple threads may try to update the counter simultaneously, causing a race condition. As a result, the final counter value may be less than expected, even though each thread performed the correct number of increments. These issues make it clear why higher-level abstractions, such as coroutines, are needed to simplify concurrency and avoid common pitfalls.

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