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semantic/bench/Main.hs

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{-# LANGUAGE DeriveAnyClass, DeriveGeneric, FlexibleInstances, StandaloneDeriving #-}
{-# OPTIONS_GHC -fno-warn-orphans #-}
module Main where
import Criterion.Main
import Data.Function
import Data.List (genericLength)
import Data.String
import Patch
import Prologue
import SES
import Test.QuickCheck hiding (Fixed)
main :: IO ()
main = do
benchmarks <- sequenceA [ generativeBenchmarkWith "ses" 10 arbitrarySESInputs (uncurry ((*) `on` length)) (nf (uncurry benchmarkSES)) ]
defaultMain benchmarks
where arbitrarySESInputs = (,) <$> sized (`vectorOf` arbitrary) <*> sized (`vectorOf` arbitrary)
benchmarkSES :: [String] -> [String] -> [Either String (Patch String)]
benchmarkSES as bs = ses compare cost as bs
where compare a b = if a == b then Just (Left a) else Nothing
cost = either (const 0) (sum . fmap genericLength)
instance NFData a => NFData (Patch a)
-- | Defines a named group of n benchmarks over inputs generated by an `Arbitrary` instance.
-- |
-- | The inputs sizes at each iteration are measured by a metric function, which gives the name of the benchmark. This makes it convenient to correlate a benchmark of some function over lists with e.g. input `length`.
generativeBenchmark :: (Arbitrary a, Show m, Ord m) => String -> Int -> (a -> m) -> (a -> Benchmarkable) -> IO Benchmark
generativeBenchmark name n metric benchmark = generativeBenchmarkWith name n arbitrary metric benchmark
generativeBenchmarkWith :: (Show m, Ord m) => String -> Int -> Gen a -> (a -> m) -> (a -> Benchmarkable) -> IO Benchmark
generativeBenchmarkWith name n generator metric benchmark = do
benchmarks <- traverse measure (take n [0,(defaultSize `div` n)..defaultSize])
pure $! bgroup name (snd <$> (sortOn fst benchmarks))
where measure n = do
input <- generate (resize n generator)
let measurement = metric input
pure $! (measurement, bench (show measurement) (benchmark input))
defaultSize = 100