Several problems:

The upshot is that the ordering makes no consistent difference (Ie. it flip flops from run to run); and that the ternary is hands down winner for the two simple scalars, common case:

use strictures; use Benchmark "cmpthese"; use List::Util "min"; # This is XS. cmpthese -1, { list_util_nb => q[ my( $x, $y ) = ( 0, 1 ); my $m = min( $x, $y +) for 1 .. 1000; ], ternary_nb => q[ my( $x, $y ) = ( 0, 1 ); my $m = $x < $y + ? $x : $y for 1 .. 1000; ], clever_nb => q[ my( $x, $y ) = ( 0, 1 ); my $m = [ $x, $y + ]->[ $x <= $y ] for 1 .. 1000; ], list_util_b => q[ my( $x, $y ) = ( 1, 0 ); my $m = min( $x, $y +) for 1 .. 1000; ], ternary_b => q[ my( $x, $y ) = ( 1, 0 ); my $m = $x < $y + ? $x : $y for 1 .. 1000; ], clever_b => q[ my( $x, $y ) = ( 1, 0 ); my $m = [ $x, $y +]->[ $x <= $y ] for 1 .. 1000; ], }; __END__ C:\test>junk30 Rate clever_b clever_nb list_util_nb list_util_b ternar +y_b ternary_nb clever_b 1210/s -- -11% -67% -70% - +79% -80% clever_nb 1356/s 12% -- -63% -67% - +76% -78% list_util_nb 3694/s 205% 172% -- -9% - +34% -40% list_util_b 4062/s 236% 200% 10% -- - +28% -33% ternary_b 5630/s 365% 315% 52% 39% + -- -8% ternary_nb 6107/s 405% 351% 65% 50% + 8% -- C:\test>junk30 Rate clever_nb clever_b list_util_b list_util_nb ternar +y_b ternary_nb clever_nb 1297/s -- -5% -68% -69% - +75% -77% clever_b 1372/s 6% -- -66% -67% - +74% -75% list_util_b 4078/s 214% 197% -- -3% - +22% -27% list_util_nb 4190/s 223% 205% 3% -- - +20% -25% ternary_b 5228/s 303% 281% 28% 25% + -- -6% ternary_nb 5556/s 328% 305% 36% 33% + 6% --

List::Util::min() will obviously win in both speed and clarity for the min( @array ) case.


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In reply to Re^3: The Boy Scout Rule by BrowserUk
in thread The Boy Scout Rule by eyepopslikeamosquito

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