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diff --git a/lib/libcxx/utils/google-benchmark/src/complexity.cc b/lib/libcxx/utils/google-benchmark/src/complexity.cc
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--- a/lib/libcxx/utils/google-benchmark/src/complexity.cc
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-// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
-//
-// 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
-//
-//     http://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.
-
-// Source project : https://github.com/ismaelJimenez/cpp.leastsq
-// Adapted to be used with google benchmark
-
-#include "benchmark/benchmark.h"
-
-#include <algorithm>
-#include <cmath>
-#include "check.h"
-#include "complexity.h"
-
-namespace benchmark {
-
-// Internal function to calculate the different scalability forms
-BigOFunc* FittingCurve(BigO complexity) {
-  static const double kLog2E = 1.44269504088896340736;
-  switch (complexity) {
-    case oN:
-      return [](int64_t n) -> double { return static_cast<double>(n); };
-    case oNSquared:
-      return [](int64_t n) -> double { return std::pow(n, 2); };
-    case oNCubed:
-      return [](int64_t n) -> double { return std::pow(n, 3); };
-    case oLogN:
-      /* Note: can't use log2 because Android's GNU STL lacks it */
-      return [](int64_t n) { return kLog2E * log(static_cast<double>(n)); };
-    case oNLogN:
-      /* Note: can't use log2 because Android's GNU STL lacks it */
-      return [](int64_t n) { return kLog2E * n * log(static_cast<double>(n)); };
-    case o1:
-    default:
-      return [](int64_t) { return 1.0; };
-  }
-}
-
-// Function to return an string for the calculated complexity
-std::string GetBigOString(BigO complexity) {
-  switch (complexity) {
-    case oN:
-      return "N";
-    case oNSquared:
-      return "N^2";
-    case oNCubed:
-      return "N^3";
-    case oLogN:
-      return "lgN";
-    case oNLogN:
-      return "NlgN";
-    case o1:
-      return "(1)";
-    default:
-      return "f(N)";
-  }
-}
-
-// Find the coefficient for the high-order term in the running time, by
-// minimizing the sum of squares of relative error, for the fitting curve
-// given by the lambda expression.
-//   - n             : Vector containing the size of the benchmark tests.
-//   - time          : Vector containing the times for the benchmark tests.
-//   - fitting_curve : lambda expression (e.g. [](int64_t n) {return n; };).
-
-// For a deeper explanation on the algorithm logic, please refer to
-// https://en.wikipedia.org/wiki/Least_squares#Least_squares,_regression_analysis_and_statistics
-
-LeastSq MinimalLeastSq(const std::vector<int64_t>& n,
-                       const std::vector<double>& time,
-                       BigOFunc* fitting_curve) {
-  double sigma_gn = 0.0;
-  double sigma_gn_squared = 0.0;
-  double sigma_time = 0.0;
-  double sigma_time_gn = 0.0;
-
-  // Calculate least square fitting parameter
-  for (size_t i = 0; i < n.size(); ++i) {
-    double gn_i = fitting_curve(n[i]);
-    sigma_gn += gn_i;
-    sigma_gn_squared += gn_i * gn_i;
-    sigma_time += time[i];
-    sigma_time_gn += time[i] * gn_i;
-  }
-
-  LeastSq result;
-  result.complexity = oLambda;
-
-  // Calculate complexity.
-  result.coef = sigma_time_gn / sigma_gn_squared;
-
-  // Calculate RMS
-  double rms = 0.0;
-  for (size_t i = 0; i < n.size(); ++i) {
-    double fit = result.coef * fitting_curve(n[i]);
-    rms += pow((time[i] - fit), 2);
-  }
-
-  // Normalized RMS by the mean of the observed values
-  double mean = sigma_time / n.size();
-  result.rms = sqrt(rms / n.size()) / mean;
-
-  return result;
-}
-
-// Find the coefficient for the high-order term in the running time, by
-// minimizing the sum of squares of relative error.
-//   - n          : Vector containing the size of the benchmark tests.
-//   - time       : Vector containing the times for the benchmark tests.
-//   - complexity : If different than oAuto, the fitting curve will stick to
-//                  this one. If it is oAuto, it will be calculated the best
-//                  fitting curve.
-LeastSq MinimalLeastSq(const std::vector<int64_t>& n,
-                       const std::vector<double>& time, const BigO complexity) {
-  CHECK_EQ(n.size(), time.size());
-  CHECK_GE(n.size(), 2);  // Do not compute fitting curve is less than two
-                          // benchmark runs are given
-  CHECK_NE(complexity, oNone);
-
-  LeastSq best_fit;
-
-  if (complexity == oAuto) {
-    std::vector<BigO> fit_curves = {oLogN, oN, oNLogN, oNSquared, oNCubed};
-
-    // Take o1 as default best fitting curve
-    best_fit = MinimalLeastSq(n, time, FittingCurve(o1));
-    best_fit.complexity = o1;
-
-    // Compute all possible fitting curves and stick to the best one
-    for (const auto& fit : fit_curves) {
-      LeastSq current_fit = MinimalLeastSq(n, time, FittingCurve(fit));
-      if (current_fit.rms < best_fit.rms) {
-        best_fit = current_fit;
-        best_fit.complexity = fit;
-      }
-    }
-  } else {
-    best_fit = MinimalLeastSq(n, time, FittingCurve(complexity));
-    best_fit.complexity = complexity;
-  }
-
-  return best_fit;
-}
-
-std::vector<BenchmarkReporter::Run> ComputeBigO(
-    const std::vector<BenchmarkReporter::Run>& reports) {
-  typedef BenchmarkReporter::Run Run;
-  std::vector<Run> results;
-
-  if (reports.size() < 2) return results;
-
-  // Accumulators.
-  std::vector<int64_t> n;
-  std::vector<double> real_time;
-  std::vector<double> cpu_time;
-
-  // Populate the accumulators.
-  for (const Run& run : reports) {
-    CHECK_GT(run.complexity_n, 0) << "Did you forget to call SetComplexityN?";
-    n.push_back(run.complexity_n);
-    real_time.push_back(run.real_accumulated_time / run.iterations);
-    cpu_time.push_back(run.cpu_accumulated_time / run.iterations);
-  }
-
-  LeastSq result_cpu;
-  LeastSq result_real;
-
-  if (reports[0].complexity == oLambda) {
-    result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity_lambda);
-    result_real = MinimalLeastSq(n, real_time, reports[0].complexity_lambda);
-  } else {
-    result_cpu = MinimalLeastSq(n, cpu_time, reports[0].complexity);
-    result_real = MinimalLeastSq(n, real_time, result_cpu.complexity);
-  }
-
-  std::string run_name = reports[0].benchmark_name().substr(
-      0, reports[0].benchmark_name().find('/'));
-
-  // Get the data from the accumulator to BenchmarkReporter::Run's.
-  Run big_o;
-  big_o.run_name = run_name;
-  big_o.run_type = BenchmarkReporter::Run::RT_Aggregate;
-  big_o.aggregate_name = "BigO";
-  big_o.iterations = 0;
-  big_o.real_accumulated_time = result_real.coef;
-  big_o.cpu_accumulated_time = result_cpu.coef;
-  big_o.report_big_o = true;
-  big_o.complexity = result_cpu.complexity;
-
-  // All the time results are reported after being multiplied by the
-  // time unit multiplier. But since RMS is a relative quantity it
-  // should not be multiplied at all. So, here, we _divide_ it by the
-  // multiplier so that when it is multiplied later the result is the
-  // correct one.
-  double multiplier = GetTimeUnitMultiplier(reports[0].time_unit);
-
-  // Only add label to mean/stddev if it is same for all runs
-  Run rms;
-  rms.run_name = run_name;
-  big_o.report_label = reports[0].report_label;
-  rms.run_type = BenchmarkReporter::Run::RT_Aggregate;
-  rms.aggregate_name = "RMS";
-  rms.report_label = big_o.report_label;
-  rms.iterations = 0;
-  rms.real_accumulated_time = result_real.rms / multiplier;
-  rms.cpu_accumulated_time = result_cpu.rms / multiplier;
-  rms.report_rms = true;
-  rms.complexity = result_cpu.complexity;
-  // don't forget to keep the time unit, or we won't be able to
-  // recover the correct value.
-  rms.time_unit = reports[0].time_unit;
-
-  results.push_back(big_o);
-  results.push_back(rms);
-  return results;
-}
-
-}  // end namespace benchmark