프로파일링 기법

Kotlin code

import kotlin.system.measureTimeMillis

class SimpleProfiler {
    private val timings = mutableMapOf<String, MutableList<Long>>()

    inline fun <T> profile(name: String, block: () -> T): T {
        val start = System.nanoTime()
        val result = block()
        val elapsed = System.nanoTime() - start
        timings.getOrPut(name) { mutableListOf() }.add(elapsed)
        return result
    }

    fun report() {
        println("=== 프로파일링 결과 ===")
        timings.entries.sortedByDescending { it.value.sum() }.forEach { (name, times) ->
            val total = times.sum() / 1_000_000.0
            val avg = total / times.size
            val max = times.max() / 1_000_000.0
            println("  $name: 총=${"%.2f".format(total)}ms, 평균=${"%.3f".format(avg)}ms, 최대=${"%.3f".format(max)}ms, 호출=${times.size}회")
        }
    }
}

fun main() {
    val profiler = SimpleProfiler()
    val data = (1..100_000).toList()

    repeat(5) {
        profiler.profile("filter+map") {
            data.filter { it % 3 == 0 }.map { it * 2 }
        }
        profiler.profile("sequence") {
            data.asSequence().filter { it % 3 == 0 }.map { it * 2 }.toList()
        }
        profiler.profile("manual loop") {
            buildList {
                for (i in data) if (i % 3 == 0) add(i * 2)
            }
        }
    }

    profiler.report()

    // JVM 메모리 상태
    val rt = Runtime.getRuntime()
    println("
메모리: 사용=${(rt.totalMemory() - rt.freeMemory()) / 1024 / 1024}MB, 최대=${rt.maxMemory() / 1024 / 1024}MB")
}