// Then - should complete quickly (this is more of a performance indicator)
        assertTrue(duration < 1000, "Creating and using 10000 EmptyIterators should be fast (took " + duration + "ms)");
    }

    @Test
    @DisplayName("EmptyIterator should work correctly in nested iteration")
    void testNestedIteration() {
        // When & Then
        assertDoesNotThrow(() -> {

        }

        if (!context.isEmpty()) {
            sb.append(", context=").append(context);
        }

        sb.append(", elapsed=").append(getElapsedTime()).append("ms");
        sb.append('}');

        return sb.toString();
    }

따라서 아래의 함수는 인자 조합마다 한 번씩 실행됩니다. 그리고 각각의 인자 조합에 대해 반환된 값은, 함수가 정확히 같은 인자 조합으로 호출될 때마다 반복해서 사용됩니다.

예를 들어 다음 함수가 있다면:

```Python
@lru_cache
def say_hi(name: str, salutation: str = "Ms."):
    return f"Hello {salutation} {name}"
```

프로그램은 다음과 같이 실행될 수 있습니다:

```mermaid
sequenceDiagram

participant code as Code
participant function as say_hi()

        // Note: Set-based O(1) lookup should be much faster than O(n) array iteration
        assertTrue("Set-based lookup should complete quickly (duration: " + duration / 1_000_000 + "ms)", duration < 1_000_000_000); // 1 second (relaxed from 100ms for CI)
    }

    /**
     * Test convertWithFieldCheck() with DEFAULT_FIELD.
     */
    @Test

        case "image/tiff" -> ".tiff";
        case "image/svg+xml" -> ".svg";
        case "image/jpeg" -> ".jpg";
        case "image/png" -> ".png";
        case "image/bmp", "image/x-windows-bmp", "image/x-ms-bmp" -> ".bmp";
        case "image/vnd.adobe.photoshop", "image/photoshop", "application/x-photoshop", "application/photoshop" -> ".psd";
        default -> "";
        };
    }

        if (parentThread != null) {
            try {
                if (logger.isDebugEnabled()) {
                    logger.debug("Waiting for crawler termination: thread={}, timeout={}ms", parentThread.getName(), millis);
                }
                parentThread.join(millis);
            } catch (final InterruptedException e) {

        crawlingInfoHelper.putToInfoMap(Constants.WEB_FS_CRAWLING_EXEC_TIME, Long.toString(execTime));
        if (logger.isInfoEnabled()) {
            logger.info("[EXEC TIME] crawling time: {}ms", execTime);
        }

        indexUpdater.setFinishCrawling(true);
        try {
            indexUpdater.join();
        } catch (final InterruptedException e) {

For example, if you have a function:

```Python
@lru_cache
def say_hi(name: str, salutation: str = "Ms."):
    return f"Hello {salutation} {name}"
```

your program could execute like this:

```mermaid
sequenceDiagram

participant code as Code
participant function as say_hi()

      .isEqualTo(1)
    assertThat(countFrames(logs, "FINE: >> 0x00000003     3 DATA          END_STREAM"))
      .isEqualTo(1)
  }

  @Test
  fun pingsTransmitted() {
    // Ping every 500 ms, starting at 500 ms.
    client =
      client
        .newBuilder()
        .pingInterval(Duration.ofMillis(500))
        .build()

    // Delay the response to give 1 ping enough time to be sent and replied to.

`@lru_cache` 會修改它所裝飾的函式，使其回傳第一次回傳的相同值，而不是每次都重新計算、執行函式碼。

因此，被裝飾的函式對於每組參數組合只會執行一次。之後，凡是以完全相同參數組合呼叫時，都會重複使用先前對應的回傳值。

例如，如果你有一個函式：

```Python
@lru_cache
def say_hi(name: str, salutation: str = "Ms."):
    return f"Hello {salutation} {name}"
```

你的程式可能會這樣執行：

```mermaid
sequenceDiagram

participant code as Code
participant function as say_hi()
participant execute as Execute function