Function stats_tpl_sample_rollthedice

freebsd/kern/subr_stats.c:1035–1080

}

int
stats_tpl_sample_rollthedice(struct stats_tpl_sample_rate *rates, int nrates,
    void *seed_bytes, size_t seed_len)
{
	uint32_t cum_pct, rnd_pct;
	int i;

	cum_pct = 0;

	/*
	 * Choose a pseudorandom or seeded number in range [0,100] and use
	 * it to make a sampling decision and template selection where required.
	 * If no seed is supplied, a PRNG is used to generate a pseudorandom
	 * number so that every selection is independent. If a seed is supplied,
	 * the caller desires random selection across different seeds, but
	 * deterministic selection given the same seed. This is achieved by
	 * hashing the seed and using the hash as the random number source.
	 *
	 * XXXLAS: Characterise hash function output distribution.
	 */
	if (seed_bytes == NULL)
		rnd_pct = random() / (INT32_MAX / 100);
	else
		rnd_pct = hash32_buf(seed_bytes, seed_len, 0) /
		    (UINT32_MAX / 100U);

	/*
	 * We map the randomly selected percentage on to the interval [0,100]
	 * consisting of the cumulatively summed template sampling percentages.
	 * The difference between the cumulative sum of all template sampling
	 * percentages and 100 is treated as a NULL assignment i.e. no stats
	 * template will be assigned, and -1 returned instead.
	 */
	for (i = 0; i < nrates; i++) {
		cum_pct += rates[i].tpl_sample_pct;

		KASSERT(cum_pct <= 100, ("%s cum_pct %u > 100", __func__,
		    cum_pct));
		if (rnd_pct > cum_pct || rates[i].tpl_sample_pct == 0)
			continue;

		return (rates[i].tpl_slot_id);
	}

	return (-1);
}

int
stats_v1_blob_clone(struct statsblobv1 **dst, size_t dstmaxsz,