Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Implementation of Hash Sets

In course

CS-108: Practice of object-oriented programming

Les étudiants perfectionnent leurs connaissances en Java et les mettent en pratique en réalisant un projet de taille conséquente. Ils apprennent à utiliser et à mettre en œuvre les principaux types de collections (listes, ensembles, tables associatives), e ...

Description

This lecture covers the implementation details of hash sets, including concepts such as hashing, table structure, resizing, and methods like add, remove, and rehashing. The instructor demonstrates the code structure using IntelliJ IDEA.

Instructor

Michel Schinz

Official source

Related concepts (32)

Hash function

A hash function is any function that can be used to map data of arbitrary size to fixed-size values, though there are some hash functions that support variable length output. The values returned by a hash function are called hash values, hash codes, digests, or simply hashes. The values are usually used to index a fixed-size table called a hash table. Use of a hash function to index a hash table is called hashing or scatter storage addressing.

Hash table

In computing, a hash table, also known as hash map, is a data structure that implements an associative array or dictionary. It is an abstract data type that maps keys to values. A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored.

Universal hashing

In mathematics and computing, universal hashing (in a randomized algorithm or data structure) refers to selecting a hash function at random from a family of hash functions with a certain mathematical property (see definition below). This guarantees a low number of collisions in expectation, even if the data is chosen by an adversary. Many universal families are known (for hashing integers, vectors, strings), and their evaluation is often very efficient.

Perfect hash function

In computer science, a perfect hash function h for a set S is a hash function that maps distinct elements in S to a set of m integers, with no collisions. In mathematical terms, it is an injective function. Perfect hash functions may be used to implement a lookup table with constant worst-case access time. A perfect hash function can, as any hash function, be used to implement hash tables, with the advantage that no collision resolution has to be implemented.

Hash collision

In computer science, a hash collision or hash clash is when two pieces of data in a hash table share the same hash value. The hash value in this case is derived from a hash function which takes a data input and returns a fixed length of bits. Although hash algorithms have been created with the intent of being collision resistant, they can still sometimes map different data to the same hash (by virtue of the pigeonhole principle). Malicious users can take advantage of this to mimic, access, or alter data.

Related lectures (35)

Implementation of Sets: Hashing

Covers the implementation of sets using hashing and set operations.

Equality, Order, and Hashing

Explains hashing, equality, and order in Java, emphasizing method compatibility for correct collection behavior.

Comparing Objects: Comparable vs Comparator

Covers the concepts of Comparable and Comparator interfaces in Java, explaining how classes implement these interfaces to enable object comparison.

Implementation of Singly Linked Lists

Covers the implementation of singly linked lists in Java, focusing on concepts such as nodes, size management, adding, removing, and getting elements.

Collections: Hashcode and Equals Methods