Intro
(See the next iteration A tiny Java framework for gathering running time statistics - Take II.)
I have this tiny Java framework that allows users to gather running time statistics of a piece of code. It gathers:
- minimum running time of a
Runnable, - maximum running time,
- mean time,
- median time,
- standard deviation.
Code
package io.github.coderodde.statistics.run;
import java.text.NumberFormat;
/**
* This class encapsulates the run statistics.
*
* @author Rodion "rodde" Efremov
*/
public final class RunStatistics {
private final long minimumDuration;
private final long maximumDuration;
private final double meanDuration;
private final double medianDuration;
private final double standardDeviation;
RunStatistics(final long minimumDuration,
final long maximumDuration,
final double meanDuration,
final double medianDuration,
final double standardDeviation) {
this.minimumDuration = minimumDuration;
this.maximumDuration = maximumDuration;
this.meanDuration = meanDuration;
this.medianDuration = medianDuration;
this.standardDeviation = standardDeviation;
}
public long getMinimumDuration() {
return minimumDuration;
}
public long getMaximumDuration() {
return maximumDuration;
}
public double getMeanDuration() {
return meanDuration;
}
public double getMedianDuration() {
return medianDuration;
}
public double getStandardDeviation() {
return standardDeviation;
}
@Override
public String toString() {
final NumberFormat nf = NumberFormat.getInstance();
return new StringBuilder("min = ")
.append(nf.format(minimumDuration))
.append(" ns, max = ")
.append(nf.format(maximumDuration))
.append(" ns, mean = ")
.append(meanDuration)
.append(" ns, median = ")
.append(medianDuration)
.append(" ns, sd = ")
.append(standardDeviation)
.append(" ns")
.toString();
}
}
package io.github.coderodde.statistics.run;
import java.util.ArrayList;
import java.util.List;
import java.util.Objects;
/**
* This class provides methods for obtaining the running time statistics.
*
* @author Rodion "rodde" Efremov
*/
public final class Runner {
private static final int MINIMUM_ITERATIONS = 1;
public static RunStatistics measure(final Runnable runnable,
final int iterations) {
Objects.requireNonNull(runnable, "The input runnable is null");
checkIterations(iterations);
long minimumDuration = Long.MAX_VALUE;
long maximumDuration = Long.MIN_VALUE;
long meanDuration = 0;
double medianDuration;
double standardDeviation;
final List<Long> durations = new ArrayList<>(iterations);
for (int iteration = 0;
iteration < iterations;
iteration++) {
final long ta = System.nanoTime();
runnable.run();
final long tb = System.nanoTime();
final long duration = tb - ta;
minimumDuration = Math.min(minimumDuration, duration);
maximumDuration = Math.max(maximumDuration, duration);
meanDuration += duration;
durations.add(duration);
}
meanDuration /= iterations;
medianDuration = computeMedianDuration(durations);
standardDeviation = computeStandardDeviation(durations, meanDuration);
return new RunStatistics(minimumDuration,
maximumDuration,
meanDuration,
medianDuration,
standardDeviation);
}
public static RunStatistics measure(final List<Runnable> runnables) {
Objects.requireNonNull(runnables, "The input runnables is null");
if (runnables.isEmpty()) {
throw new IllegalArgumentException("Nothing to measure");
}
long minimumDuration = Long.MAX_VALUE;
long maximumDuration = Long.MIN_VALUE;
long meanDuration = 0;
double medianDuration;
double standardDeviation;
final List<Long> durations = new ArrayList<>(runnables.size());
for (final Runnable runnable : runnables) {
final long ta = System.nanoTime();
runnable.run();
final long tb = System.nanoTime();
final long duration = tb - ta;
minimumDuration = Math.min(minimumDuration, duration);
maximumDuration = Math.max(maximumDuration, duration);
meanDuration += duration;
durations.add(duration);
}
meanDuration /= runnables.size();
medianDuration = computeMedianDuration(durations);
standardDeviation = computeStandardDeviation(durations, meanDuration);
return new RunStatistics(minimumDuration,
maximumDuration,
meanDuration,
medianDuration,
standardDeviation);
}
private static double computeMedianDuration(final List<Long> durations) {
if (durations.size() % 2 == 1) {
return durations.get(durations.size() / 2);
} else {
final int loIndex = durations.size() / 2 - 1;
final int hiIndex = durations.size() / 2;
return (durations.get(loIndex) + durations.get(hiIndex)) / 2.0;
}
}
private static double computeStandardDeviation(final List<Long> durations,
final long meanDuration) {
double sum = 0.0;
for (final Long duration : durations) {
sum += Math.pow(duration - meanDuration, 2.0);
}
return Math.sqrt(sum / durations.size());
}
private static void checkIterations(final int iterations) {
if (iterations < MINIMUM_ITERATIONS) {
final String exceptionMessage =
String.format("Number of iterations (%d) is too small. " +
"Must be at least %d.",
iterations,
MINIMUM_ITERATIONS);
throw new IllegalArgumentException(exceptionMessage);
}
}
}
package io.github.coderodde.statistics.run.demo;
import io.github.coderodde.statistics.run.RunStatistics;
import io.github.coderodde.statistics.run.Runner;
import java.util.Random;
public class Demo {
private static final Random RANDOM = new Random(13L);
public static void main(String[] args) {
final RunStatistics runStatistics = Runner.measure(() -> {
try {
Thread.sleep(RANDOM.nextInt(1_000));
} catch (InterruptedException ex) {}
}, 10);
System.out.println(runStatistics);
}
}
Typical output
min = 101 821 100 ns, max = 998 058 800 ns, mean = 4.9199821E8 ns, median = 5.369435E8 ns, sd = 2.965745976223299E8 ns
Critique request
Please, tell me anything that comes to mind.
