Comment by mikeckennedy
1 day ago
It is open source, you could just look. :) But here is a summary for you. It's not just one run and take the number:
Benchmark Iteration Process
Core Approach:
- Warmup Phase: 100 iterations to prepare the operation (default)
- Timing Runs: 5 repeated runs (default), each executing the operation a specified number of times
- Result: Median time per operation across the 5 runs
Iteration Counts by Operation Speed: - Very fast ops (arithmetic): 100,000 iterations per run
- Fast ops (dict/list access): 10,000 iterations per run
- Medium ops (list membership): 1,000 iterations per run
- Slower ops (database, file I/O): 1,000-5,000 iterations per run
Quality Controls:
- Garbage collection is disabled during timing to prevent interference
- Warmup runs prevent cold-start bias
- Median of 5 runs reduces noise from outliers
- Results are captured to prevent compiler optimization elimination
Total Executions: For a typical benchmark with 1,000 iterations and 5 repeats, each operation runs 5,100 times (100 warmup + 5×1,000 timed) before reporting the median result.
That answers what N is (why not just say in the article). If you are only going to report medians, is there an appendix with further statistics such as confidence intervals or standard deviations. For serious benchmark, it would be essential to show the spread or variability, no?