mirror of https://github.com/google/benchmark.git
implemented complexity reporting
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872ff01a49
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2e5c397b48
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@ -49,9 +49,11 @@ class BenchmarkReporter {
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bytes_per_second(0),
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items_per_second(0),
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max_heapbytes_used(0),
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complexity(O_1),
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complexity(O_None),
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arg1(0),
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arg2(0) {}
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arg2(0),
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report_bigO(false),
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report_rms(false) {}
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std::string benchmark_name;
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std::string report_label; // Empty if not set by benchmark.
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@ -71,6 +73,10 @@ class BenchmarkReporter {
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BigO complexity;
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int arg1;
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int arg2;
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// Inform print function if the current run is a complexity report
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bool report_bigO;
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bool report_rms;
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};
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// Called once for every suite of benchmarks run.
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@ -102,6 +108,7 @@ protected:
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static void ComputeStats(const std::vector<Run> & reports, Run& mean, Run& stddev);
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static void ComputeBigO(const std::vector<Run> & reports, Run& bigO, Run& rms);
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static TimeUnitMultiplier GetTimeUnitAndMultiplier(TimeUnit unit);
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static std::string GetBigO(BigO complexity);
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};
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// Simple reporter that outputs benchmark data to the console. This is the
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@ -88,7 +88,7 @@ void ConsoleReporter::ReportComplexity(const std::vector<Run> & complexity_repor
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Run bigO_data;
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Run rms_data;
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BenchmarkReporter::ComputeBigO(complexity_reports, bigO_data, rms_data);
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// Output using PrintRun.
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PrintRunData(bigO_data);
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PrintRunData(rms_data);
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@ -115,7 +115,22 @@ void ConsoleReporter::PrintRunData(const Run& result) {
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ColorPrintf(COLOR_GREEN, "%-*s ",
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name_field_width_, result.benchmark_name.c_str());
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if (result.iterations == 0) {
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if(result.report_bigO) {
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std::string big_o = result.report_bigO ? GetBigO(result.complexity) : "";
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ColorPrintf(COLOR_YELLOW, "%10.4f %s %10.4f %s ",
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result.real_accumulated_time * multiplier,
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big_o.c_str(),
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result.cpu_accumulated_time * multiplier,
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big_o.c_str());
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}
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else if(result.report_rms) {
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ColorPrintf(COLOR_YELLOW, "%10.0f %s %10.0f %s ",
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result.real_accumulated_time * multiplier * 100,
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"%",
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result.cpu_accumulated_time * multiplier * 100,
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"%");
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}
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else if (result.iterations == 0) {
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ColorPrintf(COLOR_YELLOW, "%10.0f %s %10.0f %s ",
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result.real_accumulated_time * multiplier,
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timeLabel,
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@ -121,13 +121,23 @@ void JSONReporter::ReportComplexity(const std::vector<Run> & complexity_reports)
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return;
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}
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std::string indent(4, ' ');
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std::ostream& out = std::cout;
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if (!first_report_) {
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out << ",\n";
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}
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Run bigO_data;
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Run rms_data;
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BenchmarkReporter::ComputeBigO(complexity_reports, bigO_data, rms_data);
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// Output using PrintRun.
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out << indent << "{\n";
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PrintRunData(bigO_data);
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out << indent << "},\n";
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out << indent << "{\n";
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PrintRunData(rms_data);
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out << indent << '}';
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}
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void JSONReporter::Finalize() {
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@ -41,7 +41,7 @@ double fittingCurve(double N, benchmark::BigO Complexity) {
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// - Complexity : Fitting curve.
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// For a deeper explanation on the algorithm logic, look the README file at http://github.com/ismaelJimenez/Minimal-Cpp-Least-Squared-Fit
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LeastSq leastSq(const std::vector<int>& N, const std::vector<int>& Time, const benchmark::BigO Complexity) {
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LeastSq leastSq(const std::vector<int>& N, const std::vector<double>& Time, const benchmark::BigO Complexity) {
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assert(N.size() == Time.size() && N.size() >= 2);
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assert(Complexity != benchmark::O_None &&
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Complexity != benchmark::O_Auto);
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@ -79,7 +79,7 @@ LeastSq leastSq(const std::vector<int>& N, const std::vector<int>& Time, const b
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double mean = sigmaTime / N.size();
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result.rms = sqrt(rms) / mean; // Normalized RMS by the mean of the observed values
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result.rms = sqrt(rms / N.size()) / mean; // Normalized RMS by the mean of the observed values
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return result;
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}
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@ -90,7 +90,7 @@ LeastSq leastSq(const std::vector<int>& N, const std::vector<int>& Time, const b
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// - Complexity : If different than O_Auto, the fitting curve will stick to this one. If it is O_Auto, it will be calculated
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// the best fitting curve.
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LeastSq minimalLeastSq(const std::vector<int>& N, const std::vector<int>& Time, const benchmark::BigO Complexity) {
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LeastSq minimalLeastSq(const std::vector<int>& N, const std::vector<double>& Time, const benchmark::BigO Complexity) {
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assert(N.size() == Time.size() && N.size() >= 2); // Do not compute fitting curve is less than two benchmark runs are given
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assert(Complexity != benchmark::O_None); // Check that complexity is a valid parameter.
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@ -41,6 +41,6 @@ struct LeastSq {
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};
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// Find the coefficient for the high-order term in the running time, by minimizing the sum of squares of relative error.
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LeastSq minimalLeastSq(const std::vector<int>& N, const std::vector<int>& Time, const benchmark::BigO Complexity = benchmark::O_Auto);
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LeastSq minimalLeastSq(const std::vector<int>& N, const std::vector<double>& Time, const benchmark::BigO Complexity = benchmark::O_Auto);
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#endif
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@ -17,6 +17,7 @@
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#include <cstdlib>
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#include <vector>
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#include <tuple>
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#include "check.h"
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#include "stat.h"
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@ -83,35 +84,67 @@ void BenchmarkReporter::ComputeBigO(
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Run& bigO, Run& rms) {
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CHECK(reports.size() >= 2) << "Cannot compute asymptotic complexity for less than 2 reports";
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// Accumulators.
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Stat1_d real_accumulated_time_stat;
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Stat1_d cpu_accumulated_time_stat;
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std::vector<int> N;
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std::vector<double> RealTime;
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std::vector<double> CpuTime;
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// Populate the accumulators.
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for (Run const& run : reports) {
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real_accumulated_time_stat +=
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Stat1_d(run.real_accumulated_time/run.iterations, run.iterations);
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cpu_accumulated_time_stat +=
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Stat1_d(run.cpu_accumulated_time/run.iterations, run.iterations);
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N.push_back(run.arg1);
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RealTime.push_back(run.real_accumulated_time/run.iterations);
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CpuTime.push_back(run.cpu_accumulated_time/run.iterations);
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}
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LeastSq resultCpu = minimalLeastSq(N, CpuTime, reports[0].complexity);
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// resultCpu.complexity is passed as parameter to resultReal because in case
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// reports[0].complexity is O_Auto, the noise on the measured data could make
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// the best fit function of Cpu and Real differ. In order to solve this, we take
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// the best fitting function for the Cpu, and apply it to Real data.
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LeastSq resultReal = minimalLeastSq(N, RealTime, resultCpu.complexity);
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std::string benchmark_name = reports[0].benchmark_name.substr(0, reports[0].benchmark_name.find('/'));
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// Get the data from the accumulator to BenchmarkReporter::Run's.
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bigO.benchmark_name = benchmark_name + "_BigO";
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bigO.iterations = 0;
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bigO.real_accumulated_time = real_accumulated_time_stat.Mean();
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bigO.cpu_accumulated_time = cpu_accumulated_time_stat.Mean();
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bigO.real_accumulated_time = resultReal.coef;
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bigO.cpu_accumulated_time = resultCpu.coef;
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bigO.report_bigO = true;
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bigO.complexity = resultCpu.complexity;
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double multiplier;
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const char* timeLabel;
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std::tie(timeLabel, multiplier) = GetTimeUnitAndMultiplier(reports[0].time_unit);
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// Only add label to mean/stddev if it is same for all runs
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bigO.report_label = reports[0].report_label;
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rms.benchmark_name = benchmark_name + "_RMS";
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rms.report_label = bigO.report_label;
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rms.iterations = 0;
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rms.real_accumulated_time =
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real_accumulated_time_stat.StdDev();
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rms.cpu_accumulated_time =
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cpu_accumulated_time_stat.StdDev();
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rms.real_accumulated_time = resultReal.rms / multiplier;
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rms.cpu_accumulated_time = resultCpu.rms / multiplier;
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rms.report_rms = true;
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rms.complexity = resultCpu.complexity;
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}
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std::string BenchmarkReporter::GetBigO(BigO complexity) {
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switch (complexity) {
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case O_N:
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return "* N";
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case O_N_Squared:
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return "* N**2";
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case O_N_Cubed:
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return "* N**3";
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case O_log_N:
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return "* lgN";
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case O_N_log_N:
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return "* NlgN";
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case O_1:
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return "* 1";
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default:
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return "";
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}
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}
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TimeUnitMultiplier BenchmarkReporter::GetTimeUnitAndMultiplier(TimeUnit unit) {
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@ -27,7 +27,7 @@ void BM_Complexity_O1(benchmark::State& state) {
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while (state.KeepRunning()) {
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}
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}
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BENCHMARK(BM_Complexity_O1) -> Range(1, 1<<17) -> Complexity(benchmark::O_1);
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BENCHMARK(BM_Complexity_O1) -> Range(1, 1<<18) -> Complexity(benchmark::O_1);
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static void BM_Complexity_O_N(benchmark::State& state) {
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auto v = ConstructRandomVector(state.range_x());
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@ -36,9 +36,9 @@ static void BM_Complexity_O_N(benchmark::State& state) {
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benchmark::DoNotOptimize(std::find(v.begin(), v.end(), itemNotInVector));
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}
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}
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BENCHMARK(BM_Complexity_O_N) -> Range(1, 1<<10) -> Complexity(benchmark::O_N);
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BENCHMARK(BM_Complexity_O_N) -> Range(1, 1<<10) -> Complexity(benchmark::O_Auto);
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BENCHMARK(BM_Complexity_O_N) -> RangeMultiplier(2)->Range(1<<10, 1<<16) -> Complexity(benchmark::O_N);
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BENCHMARK(BM_Complexity_O_N) -> RangeMultiplier(2)->Range(1<<10, 1<<16) -> Complexity(benchmark::O_Auto);
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static void BM_Complexity_O_N_Squared(benchmark::State& state) {
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std::string s1(state.range_x(), '-');
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std::string s2(state.range_x(), '-');
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@ -76,7 +76,8 @@ static void BM_Complexity_O_log_N(benchmark::State& state) {
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benchmark::DoNotOptimize(m.find(itemNotInVector));
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}
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}
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BENCHMARK(BM_Complexity_O_log_N) -> Range(1, 1<<10) -> Complexity(benchmark::O_log_N);
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BENCHMARK(BM_Complexity_O_log_N)
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->RangeMultiplier(2)->Range(1<<10, 1<<16) -> Complexity(benchmark::O_log_N);
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static void BM_Complexity_O_N_log_N(benchmark::State& state) {
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auto v = ConstructRandomVector(state.range_x());
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@ -84,10 +85,10 @@ static void BM_Complexity_O_N_log_N(benchmark::State& state) {
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std::sort(v.begin(), v.end());
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}
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}
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BENCHMARK(BM_Complexity_O_N_log_N) -> Range(1, 1<<16) -> Complexity(benchmark::O_N_log_N);
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BENCHMARK(BM_Complexity_O_N_log_N) -> Range(1, 1<<16) -> Complexity(benchmark::O_Auto);
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BENCHMARK(BM_Complexity_O_N_log_N) ->RangeMultiplier(2)->Range(1<<10, 1<<16) -> Complexity(benchmark::O_N_log_N);
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BENCHMARK(BM_Complexity_O_N_log_N) ->RangeMultiplier(2)->Range(1<<10, 1<<16) -> Complexity(benchmark::O_Auto);
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// Test benchmark with no range. Complexity is always calculated as O(1).
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// Test benchmark with no range and check no complexity is calculated.
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void BM_Extreme_Cases(benchmark::State& state) {
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while (state.KeepRunning()) {
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}
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