Changelog of @hackage/golds-gym 0.5.0.0

Changelog

Clarified copyright notice for vendored code from tasty-bench, (c) Andrew Lelechenko 2021 -

BREAKING: Removed whnf (weak head normal form) evaluation combinators, the library is geared towards non-infinite input data
- Removed whnf - use nf instead for pure functions
- Removed whnfIO - use nfIO instead for IO actions
- Removed whnfAppIO - use nfAppIO instead for functions returning IO
- Migration: Replace all whnf* calls with their nf* equivalents

QuickCheck property tests for statistical computations in Runner module
- 28 property tests covering mathematical invariants and edge cases
- Tests for calculateTrimmedMean, calculateMAD, calculateIQR, detectOutliers
- Tests for compareStats tolerance logic (hybrid percentage/absolute)
- Tests for checkVariance warning generation
- Custom generators for valid timing data and benchmark configurations
- New test suite: golds-gym-properties
Evaluation strategy combinators for proper laziness handling
- nf - Force result to normal form (deep evaluation)
- nfIO - Normal form for IO actions
- nfAppIO - Normal form for functions returning IO
- io - Plain IO action (for backward compatibility)
- Vendored evaluation loops from tasty-bench with attribution
BenchAction type wrapping Word64 -> IO () for benchmarkable actions
- Enables direct benchmarking of pure functions without manual evaluate calls

BREAKING: All benchmark API functions now accept BenchAction instead of IO ()
- benchGolden :: String -> BenchAction -> Spec
- benchGoldenWith :: BenchConfig -> String -> BenchAction -> Spec
- benchGoldenWithExpectation :: String -> BenchConfig -> [Expectation] -> BenchAction -> Spec
- Migration: wrap existing IO () actions with io combinator
- New: use nf/whnf for pure functions instead of manual evaluate
Output format: Baseline now appears before Actual in comparison tables
Error messages: Tolerance values in failure messages are now extracted from expectations rather than config defaults

Evaluation strategy bug where GHC could share computation across benchmark iterations
Error message wording for performance improvements (now says "decreased by" instead of "increased by -X%")
Flaky micro-benchmarks stabilized by increasing iteration counts (500-2000 iterations)

Lens-based expectation combinators for custom performance assertions
- New Test.Hspec.BenchGolden.Lenses module with van Laarhoven lenses for GoldenStats fields
- Lenses: _statsMean, _statsMedian, _statsTrimmedMean, _statsStddev, _statsMAD, _statsIQR, _statsMin, _statsMax
- Smart metric selectors: metricFor and varianceFor automatically choose appropriate lens based on BenchConfig
- Expectation type for composable performance assertions
- Tolerance variants: Percent, Absolute, Hybrid, MustImprove, MustRegress
- Boolean composition operators: (&&~) for AND, (||~) for OR
- Infix operators: (@~) for percentage, (@<) for absolute, (@<<) for must-improve, (@>>) for must-regress
- benchGoldenWithExpectation combinator for custom lens-based expectations
- Enables assertions like "must be 10% faster", "median within 10%", "IQR < 0.1ms"
Tolerance helper functions for manual comparison
- withinPercent, withinAbsolute, withinHybrid for tolerance checking
- mustImprove, mustRegress for directional performance expectations
- percentDiff, absDiff utilities

Refactored comparison logic to use lenses internally (non-breaking)
- compareStats now uses metricFor instead of if/else branching
- checkVariance now uses varianceFor for cleaner metric selection

Hybrid tolerance mechanism to prevent false failures from measurement noise
- New absoluteToleranceMs field in BenchConfig (default: Just 0.01 ms)
- Benchmarks now pass if EITHER percentage tolerance OR absolute tolerance is satisfied
- Eliminates random failures for sub-millisecond operations where measurement noise causes large percentage variations despite negligible absolute differences
Enhanced failure messages showing both tolerance thresholds
- Regression/improvement messages now display: "tolerance: 15.0% or 0.010 ms" when absolute tolerance is configured
Example benchmarks demonstrating tolerance configurations
- Hybrid tolerance (default)
- Percentage-only tolerance
- Strict absolute tolerance
- Relaxed tolerance for CI environments

Default BenchConfig now includes absoluteToleranceMs = Just 0.01 (10 microseconds)
BenchResult constructors (Regression, Improvement) now include Maybe Double for absolute tolerance
Updated "sort already sorted" example to use robust statistics to handle outliers
Increased tolerance for percentage-only example to 30% to reduce false failures

Random benchmark failures for fast operations (< 1ms) due to measurement noise
False regressions when absolute time differences are negligible but percentage variations are large
Inconsistent test results across runs for sub-millisecond operations