I'm comparing two nearly identical XOR-based hash functions in JavaScript. In the first version, the string length is stored once and the loop counts upward. In the second, the loop starts at the last character and counts down while checking whether the index is nonnegative. I expected the downward version to be faster because the upward version might need to evaluate the string length on every iteration, but my measurements suggest otherwise. Is there a meaningful performance difference between these loop forms, or is the result mainly a benchmarking and JavaScript-engine optimization issue?
3 Answers
The loop direction probably isn’t the real explanation. Modern JavaScript engines can optimize, inline, or compile these functions differently depending on the engine, runtime version, warm-up state, and which function runs first. Since the test discards the results of map(), the benchmark may also be affected by optimization decisions. Run each function many times, warm up the code first, alternate the order, keep the results observable, and use a benchmarking tool. In practice, these two loops should be very close.
Use a proper benchmark with many samples and a warm-up phase instead of timing one call to each function. Benchmark.js or a similar tool can handle repeated runs and reduce the impact of JIT compilation and timing noise. Also make sure the hash results are consumed somehow so the work cannot be treated as dead or irrelevant. Unless measurements consistently show a significant difference in a controlled environment, choose the clearer loop rather than relying on a micro-optimization.
Both versions do essentially the same amount of work: one reads the length once before the loop, while the other compares the index with zero. The JavaScript engine can often eliminate or simplify repeated property access anyway, especially when the string is known to be stable. Differences in garbage collection, CPU caching, JIT compilation, and startup effects can easily be larger than the loop difference.
A single hot function can still be expensive if it runs often, but it’s better to first check whether the function is called unnecessarily or whether the overall algorithm and memory usage can be improved.
I’ve seen the winner change just by switching the order of the tests or repeating them. That suggests measurement noise and JIT behavior rather than a reliable advantage for counting in either direction.