Candidatos:
Randomized Quicksort: By picking a pivot uniformly at random, this algorithm avoids the
worst-case performance of naive quicksort on sorted data, ensuring
expected time.
Randomized Hashing: Randomly selecting a hash function from a universal family ensures that the probability of any two keys colliding is low, providing
expected lookup time.
Candidatos:
Randomized Quicksort: By picking a pivot uniformly at random, this algorithm avoids the
worst-case performance of naive quicksort on sorted data, ensuring
expected time.
Randomized Hashing: Randomly selecting a hash function from a universal family ensures that the probability of any two keys colliding is low, providing
expected lookup time.