Testing code that utilizes the Just-In-Time (JIT) compiler can be quite different from testing traditional interpreted code. JIT compilers convert bytecode into native machine code at runtime, which means performance and behavior can vary based on numerous factors including the JIT optimizations being applied. Here are a few strategies to effectively test such code:
Below is an example of testing an application that uses the JIT compiler:
<?php
// Example function to test
function add($a, $b) {
return $a + $b;
}
// Unit test
class AddTest extends PHPUnit\Framework\TestCase {
public function testAdd() {
$this->assertEquals(5, add(2, 3));
$this->assertEquals(0, add(-1, 1));
}
}
// Performance test
function performanceTest() {
$start = microtime(true);
for ($i = 0; $i < 1000000; $i++) {
add(1, 1);
}
$end = microtime(true);
echo "Performance test duration: " . ($end - $start) . " seconds.";
}
performanceTest();
?>
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?