criterion performance measurements


want to understand this report?


lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 5.54613319607341e-3 5.621667703915931e-3 5.713526073454561e-3
Standard deviation 1.972562820146363e-4 2.494938876886024e-4 3.1487131555210624e-4

Outlying measurements have moderate (0.21993690418913867%) effect on estimated standard deviation.

understanding this report

In this report, each function benchmarked by criterion is assigned a section of its own. The charts in each section are active; if you hover your mouse over data points and annotations, you will see more details.

Under the charts is a small table. The first two rows are the results of a linear regression run on the measurements displayed in the right-hand chart.

We use a statistical technique called the bootstrap to provide confidence intervals on our estimates. The bootstrap-derived upper and lower bounds on estimates let you see how accurate we believe those estimates to be. (Hover the mouse over the table headers to see the confidence levels.)

A noisy benchmarking environment can cause some or many measurements to fall far from the mean. These outlying measurements can have a significant inflationary effect on the estimate of the standard deviation. We calculate and display an estimate of the extent to which the standard deviation has been inflated by outliers.