What does the concept of a collision mean in the context of hashing?

Question

BlackTom AI · Accepted Answer

To understand hashing collisions, we start by clarifying what a collision means in this context.
Option a: 'When given two distinct keys x1 and x2, the hash value is identical, i.e. h(x1)=h(x2)'. This directly captures the formal definition: two different inputs producing the same hash output.
Option b: 'When given two distinct keys x1 and x2, the hash value is different, i.e. h(x1)≠h(x2)'. This is the opposite of a collision; it describes a situation where no collision occurs between those two keys, so it is incorrect as the definition.
Option c: 'When the slot at the hashed position is already taken by another key'. This describes a practical consequence or manifestation of a collision during insertion (e.g., in open addressing, you encounter a filled slot and must probe). While related, it is not the formal definition of a collision itself, so it’s not the best answer to define the concept.
Option d: 'When the use of the function leads to clustering'. Clustering refers to a phenomenon where hash values group together due to patterns in the distribution or probing strategy, which is an effect that can accompany hashing, not the definition of a collision.
Overall, option a correctly defines a collision as two distinct keys mapping to the same hash value, while the other options describe related ideas or consequences but do not define the concept itself.

What does the concept of a collision mean in the context of hashing?Single choice

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