t khẩu chưa đủ độ phức tạp",badNumberOfSelectedOptionsStart:"Bạn cần tích chọn ít nhất ",badNumberOfSelectedOptionsEnd:" lựa chọn",badAlphaNumeric:"Yêu cầu chỉ nhập chữ hoặc số ",badAlphaNumericExtra:" và ",wrongFileSize:"File của bạn quá lớn (chỉ chấp nhận file không quá %s)",wrongFileType:"Chỉ cho phép các định dạng file sau: %s",groupCheckedRangeStart:"Vui lòng tích chọn từ ",groupCheckedTooFewStart:"Vui lòng tích chọn ít nhất ",groupCheckedTooManyStart:"Vui lòng tích chọn nhiều nhất ",groupCheckedEnd:"...

  testImplementation(libs.kotlin.junit5)
  testImplementation(libs.junit.jupiter.params)
}

graalvmNative {
  testSupport = true

  binaries {
    named("test") {
      buildArgs.add("--strict-image-heap")

      // speed up development testing
      buildArgs.add("-Ob")
    }
  }

 * Reader implementations, this compares the performance of the different options.
 */
// These benchmarks allocate a lot of data so use a large heap
@VmOptions({"-Xms12g", "-Xmx12g", "-d64"})
@NullUnmarked
public class CharStreamsCopyBenchmark {
  enum CopyStrategy {
    OLD {
      @Override
      long copy(Readable from, Appendable to) throws IOException {

                    if (os == Os.WINDOWS) {
                        listOf("jprofiler")
                    } else {
                        listOf("async-profiler", "async-profiler-heap")
                    }.map { FlameGraphGenerationBuildSpec(scenario, os, arch, it) }
                }
            }

    inner class FlameGraphGenerationBuildSpec(

        allowEmpty = false,
        description =
            "Command line option for the performance test task to enable profiling. " +
                "For example `async-profiler`, `async-profiler-heap`, `async-profiler-wall`, `async-profiler-all` or `jfr`. Use `none` for benchmarking only.",
    )
}

object AdHocPerformanceScenarioLinux : AdHocPerformanceScenario(Os.LINUX)

@NullMarked
public final class GcFinalization {
  private GcFinalization() {}

  /**
   * 10 seconds ought to be long enough for any object to be GC'ed and finalized. Unless we have a
   * gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but

        String url = "http://example.com/large-dataset";
        String message = "Crawling failed due to memory exhaustion";
        OutOfMemoryError error = new OutOfMemoryError("Heap space exhausted");

        DataStoreCrawlingException exception = new DataStoreCrawlingException(url, message, error);

        assertEquals(url, exception.getUrl());

        final long maxBytes = runtime.maxMemory();
        final long totalBytes = runtime.totalMemory();
        final long usedBytes = totalBytes - freeBytes;
        return "Mem:{used " + byteCountToDisplaySize(usedBytes) + ", heap " + byteCountToDisplaySize(totalBytes) + ", max "
                + byteCountToDisplaySize(maxBytes) + "}";
    }

    /**
     * Converts byte count to human-readable size format.
     *

import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks for various potential implementations of {@code ByteSource.asCharSource(...).read()}.
 */
// These benchmarks allocate a lot of data so use a large heap
@VmOptions({"-Xms12g", "-Xmx12g", "-d64"})
@NullUnmarked
public class ByteSourceAsCharSourceReadBenchmark {
  enum ReadStrategy {
    TO_BYTE_ARRAY_NEW_STRING {
      @Override

import org.jspecify.annotations.NullUnmarked;

/**
 * Benchmarks for various potential implementations of {@code ByteSource.asCharSource(...).read()}.
 */
// These benchmarks allocate a lot of data so use a large heap
@VmOptions({"-Xms12g", "-Xmx12g", "-d64"})
@NullUnmarked
public class ByteSourceAsCharSourceReadBenchmark {
  enum ReadStrategy {
    TO_BYTE_ARRAY_NEW_STRING {
      @Override