Compiling liblevenshtein v0.1.0 (/home/dylon/Workspace/f1r3fly.io/liblevenshtein-rust) warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:71:21 | 71 | let mut dawg = DynamicDawg::default(); | ----^^^^ | | | help: remove this `mut` | = note: `#[warn(unused_mut)]` on by default warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:160:21 | 160 | let mut dawg_clone = dawg.clone(); | ----^^^^^^^^^^ | | | help: remove this `mut` warning: variable does not need to be mutable --> benches/dawg_benchmarks.rs:152:13 | 152 | let mut dawg = DynamicDawg::default(); | ----^^^^ | | | help: remove this `mut` warning: `liblevenshtein` (bench "dawg_benchmarks") generated 3 warnings (run `cargo fix --bench "dawg_benchmarks"` to apply 3 suggestions) Finished `bench` profile [optimized + debuginfo] target(s) in 44.16s Running benches/dawg_benchmarks.rs (target/release/deps/dawg_benchmarks-6005c94a1d9b6dc5) Benchmarking dawg_edge_iteration/100 Benchmarking dawg_edge_iteration/100: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/100: Collecting 100 samples in estimated 5.0018 s (3.2M iterations) Benchmarking dawg_edge_iteration/100: Analyzing dawg_edge_iteration/100 time: [1.5519 µs 1.5654 µs 1.5795 µs] thrpt: [63.311 Melem/s 63.882 Melem/s 64.438 Melem/s] change: time: [-26.790% -26.022% -25.251%] (p = 0.00 < 0.05) thrpt: [+33.782% +35.175% +36.594%] Performance has improved. Found 1 outliers among 100 measurements (1.00%) 1 (1.00%) high mild Benchmarking dawg_edge_iteration/500 Benchmarking dawg_edge_iteration/500: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/500: Collecting 100 samples in estimated 5.0012 s (3.2M iterations) Benchmarking dawg_edge_iteration/500: Analyzing dawg_edge_iteration/500 time: [1.5566 µs 1.5628 µs 1.5700 µs] thrpt: [318.48 Melem/s 319.93 Melem/s 321.20 Melem/s] change: time: [-20.574% -19.947% -19.352%] (p = 0.00 < 0.05) thrpt: [+23.996% +24.917% +25.903%] Performance has improved. Found 7 outliers among 100 measurements (7.00%) 1 (1.00%) low mild 5 (5.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_iteration/1000 Benchmarking dawg_edge_iteration/1000: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/1000: Collecting 100 samples in estimated 5.0002 s (3.2M iterations) Benchmarking dawg_edge_iteration/1000: Analyzing dawg_edge_iteration/1000 time: [1.5666 µs 1.5716 µs 1.5770 µs] thrpt: [634.10 Melem/s 636.29 Melem/s 638.32 Melem/s] change: time: [-22.063% -21.312% -20.601%] (p = 0.00 < 0.05) thrpt: [+25.946% +27.085% +28.308%] Performance has improved. Found 8 outliers among 100 measurements (8.00%) 7 (7.00%) high mild 1 (1.00%) high severe Benchmarking dawg_edge_iteration/5000 Benchmarking dawg_edge_iteration/5000: Warming up for 3.0000 s Benchmarking dawg_edge_iteration/5000: Collecting 100 samples in estimated 5.0059 s (3.3M iterations) Benchmarking dawg_edge_iteration/5000: Analyzing dawg_edge_iteration/5000 time: [1.5396 µs 1.5451 µs 1.5518 µs] thrpt: [3.2221 Gelem/s 3.2360 Gelem/s 3.2476 Gelem/s] change: time: [-22.444% -21.666% -20.914%] (p = 0.00 < 0.05) thrpt: [+26.444% +27.659% +28.939%] Performance has improved. Found 9 outliers among 100 measurements (9.00%) 8 (8.00%) high mild 1 (1.00%) high severe