criterion performance measurements

overview

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lexers/ctk

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 0.31008955892763906 0.31095922526596964 0.3121579783470987
Standard deviation 4.625707029289605e-4 1.1460578712828749e-3 1.4742777384506875e-3

Outlying measurements have moderate (0.16%) effect on estimated standard deviation.

lexers/trie

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 0.2647149760218772 0.26730971807181364 0.26934530796360473
Standard deviation 1.291306596092683e-3 2.522577129185732e-3 3.045262498270923e-3

Outlying measurements have moderate (0.15999999999999992%) 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.