https://github.com/bodigrim/tasty-bench-fit

Benchmark a given function for variable input sizes and find out its time complexity
https://github.com/bodigrim/tasty-bench-fit

algorithm-analysis algorithm-complexity asymptotics benchmark-framework complexity-analysis haskell nonlinear-regression performance-analysis performance-measurement performance-testing regression time-complexity time-complexity-analysis

Last synced: 10 days ago
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Benchmark a given function for variable input sizes and find out its time complexity

• Host: GitHub
• URL: https://github.com/bodigrim/tasty-bench-fit
• Owner: Bodigrim
• License: mit
• Created: 2023-04-04T00:00:56.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-07-08T23:17:48.000Z (4 months ago)
• Last Synced: 2024-10-13T10:34:45.360Z (24 days ago)
• Topics: algorithm-analysis, algorithm-complexity, asymptotics, benchmark-framework, complexity-analysis, haskell, nonlinear-regression, performance-analysis, performance-measurement, performance-testing, regression, time-complexity, time-complexity-analysis
• Language: Haskell
• Homepage:
• Size: 20.5 KB
• Stars: 25
• Watchers: 4
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# tasty-bench-fit

Benchmark a given function for variable input sizes and find out its time complexity.

```haskell

> fit $ mkFitConfig (\x -> sum [1..x]) (10, 10000)

1.2153e-8 * x

> fit $ mkFitConfig (\x -> Data.List.nub [1..x]) (10, 10000)

2.8369e-9 * x ^ 2

> fit $ mkFitConfig (\x -> Data.List.sort $ take (fromIntegral x) $ iterate (\n -> n * 6364136223846793005 + 1) (1 :: Int)) (10, 100000)

5.2990e-8 * x * log x

```

One can usually get reliable results for functions, which do not allocate much: like in-place vector sort or fused list operations like `sum [1..x]`.

Unfortunately, fitting functions, which allocate a lot, is likely to be disappointing: GC kicks in irregularly depending on nursery and heap sizes and often skews observations beyond any recognition. Consider running such measurements with `-O0` or in `ghci` prompt. This is how the usage example above was generated. Without optimizations your program allocates much more and triggers GC regularly, somewhat evening out its effect.