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diff --git a/third_party/abseil-cpp/absl/strings/internal/cordz_functions_test.cc b/third_party/abseil-cpp/absl/strings/internal/cordz_functions_test.cc
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+++ b/third_party/abseil-cpp/absl/strings/internal/cordz_functions_test.cc
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+// Copyright 2019 The Abseil Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "absl/strings/internal/cordz_functions.h"
+
+#include <thread>  // NOLINT we need real clean new threads
+
+#include "gmock/gmock.h"
+#include "gtest/gtest.h"
+#include "absl/base/config.h"
+
+namespace absl {
+ABSL_NAMESPACE_BEGIN
+namespace cord_internal {
+namespace {
+
+using ::testing::Eq;
+using ::testing::Ge;
+using ::testing::Le;
+
+TEST(CordzFunctionsTest, SampleRate) {
+  int32_t orig_sample_rate = get_cordz_mean_interval();
+  int32_t expected_sample_rate = 123;
+  set_cordz_mean_interval(expected_sample_rate);
+  EXPECT_THAT(get_cordz_mean_interval(), Eq(expected_sample_rate));
+  set_cordz_mean_interval(orig_sample_rate);
+}
+
+// Cordz is disabled when we don't have thread_local. All calls to
+// should_profile will return false when cordz is diabled, so we might want to
+// avoid those tests.
+#ifdef ABSL_INTERNAL_CORDZ_ENABLED
+
+TEST(CordzFunctionsTest, ShouldProfileDisable) {
+  int32_t orig_sample_rate = get_cordz_mean_interval();
+
+  set_cordz_mean_interval(0);
+  cordz_set_next_sample_for_testing(0);
+  EXPECT_FALSE(cordz_should_profile());
+  // 1 << 16 is from kIntervalIfDisabled in cordz_functions.cc.
+  EXPECT_THAT(cordz_next_sample, Eq(1 << 16));
+
+  set_cordz_mean_interval(orig_sample_rate);
+}
+
+TEST(CordzFunctionsTest, ShouldProfileAlways) {
+  int32_t orig_sample_rate = get_cordz_mean_interval();
+
+  set_cordz_mean_interval(1);
+  cordz_set_next_sample_for_testing(1);
+  EXPECT_TRUE(cordz_should_profile());
+  EXPECT_THAT(cordz_next_sample, Le(1));
+
+  set_cordz_mean_interval(orig_sample_rate);
+}
+
+TEST(CordzFunctionsTest, DoesNotAlwaysSampleFirstCord) {
+  // Set large enough interval such that the chance of 'tons' of threads
+  // randomly sampling the first call is infinitely small.
+  set_cordz_mean_interval(10000);
+  int tries = 0;
+  bool sampled = false;
+  do {
+    ++tries;
+    ASSERT_THAT(tries, Le(1000));
+    std::thread thread([&sampled] {
+      sampled = cordz_should_profile();
+    });
+    thread.join();
+  } while (sampled);
+}
+
+TEST(CordzFunctionsTest, ShouldProfileRate) {
+  static constexpr int kDesiredMeanInterval = 1000;
+  static constexpr int kSamples = 10000;
+  int32_t orig_sample_rate = get_cordz_mean_interval();
+
+  set_cordz_mean_interval(kDesiredMeanInterval);
+
+  int64_t sum_of_intervals = 0;
+  for (int i = 0; i < kSamples; i++) {
+    // Setting next_sample to 0 will force cordz_should_profile to generate a
+    // new value for next_sample each iteration.
+    cordz_set_next_sample_for_testing(0);
+    cordz_should_profile();
+    sum_of_intervals += cordz_next_sample;
+  }
+
+  // The sum of independent exponential variables is an Erlang distribution,
+  // which is a gamma distribution where the shape parameter is equal to the
+  // number of summands. The distribution used for cordz_should_profile is
+  // actually floor(Exponential(1/mean)) which introduces bias. However, we can
+  // apply the squint-really-hard correction factor. That is, when mean is
+  // large, then if we squint really hard the shape of the distribution between
+  // N and N+1 looks like a uniform distribution. On average, each value for
+  // next_sample will be about 0.5 lower than we would expect from an
+  // exponential distribution. This squint-really-hard correction approach won't
+  // work when mean is smaller than about 10 but works fine when mean is 1000.
+  //
+  // We can use R to calculate a confidence interval. This
+  // shows how to generate a confidence interval with a false positive rate of
+  // one in a billion.
+  //
+  // $ R -q
+  // > mean = 1000
+  // > kSamples = 10000
+  // > errorRate = 1e-9
+  // > correction = -kSamples / 2
+  // > low = qgamma(errorRate/2, kSamples, 1/mean) + correction
+  // > high = qgamma(1 - errorRate/2, kSamples, 1/mean) + correction
+  // > low
+  // [1] 9396115
+  // > high
+  // [1] 10618100
+  EXPECT_THAT(sum_of_intervals, Ge(9396115));
+  EXPECT_THAT(sum_of_intervals, Le(10618100));
+
+  set_cordz_mean_interval(orig_sample_rate);
+}
+
+#else  // ABSL_INTERNAL_CORDZ_ENABLED
+
+TEST(CordzFunctionsTest, ShouldProfileDisabled) {
+  int32_t orig_sample_rate = get_cordz_mean_interval();
+
+  set_cordz_mean_interval(1);
+  cordz_set_next_sample_for_testing(0);
+  EXPECT_FALSE(cordz_should_profile());
+
+  set_cordz_mean_interval(orig_sample_rate);
+}
+
+#endif  // ABSL_INTERNAL_CORDZ_ENABLED
+
+}  // namespace
+}  // namespace cord_internal
+ABSL_NAMESPACE_END
+}  // namespace absl