Data Structures and Algorithms Review

Vocabulary flashcards summarizing key concepts from the lecture on data structures and algorithms.

Data Structure

A specialized format for organizing, processing, retrieving, and storing data.

Linear Data Structure

A data structure with homogeneous elements arranged in a linear sequence.

Array

A sequence of finite items of the same data type stored contiguously in memory, accessed by indexing.

Linked List

A sequence of nodes where each node contains data and links to other nodes.

Singly Linked List

A linked list where each node points to the next node.

Doubly Linked List

A linked list where each node points to both its predecessor and successor.

Stack

A linear data structure that follows the LIFO (Last In, First Out) principle.

Push operation

The process of adding an element to the top of a stack.

Pop operation

The process of removing the top element from a stack.

Reverse Polish Notation (RPN)

A notation where every operator follows all of its operands.

Queue

A data structure where items are added at one end (rear) and removed from another end (front) following FIFO (First In, First Out).

Enqueue operation

The process of adding an element to the rear of a queue.

Dequeue operation

The process of removing an element from the front of a queue.

Non-linear Data Structure

A data structure that does not organize data sequentially, exhibiting hierarchical relationships.

Tree

A connected acyclic graph with nodes and edges, where each node has at most two children.

Binary Search Tree

A binary tree in which every node has lesser values on the left and greater on the right.

AVL Tree

A self-balancing binary search tree where the balance factor is maintained.

Hashing

The process of converting data into a shorter fixed-length key representing the original value.

Graph

A collection of vertices and edges connecting them.

Directed Graph

A graph where edges have a direction.

Algorithm

A sequence of unambiguous instructions for solving a problem.

Criteria of a Good Algorithm

Conditions such as input, output, finiteness, definiteness, and effectiveness that determine the quality of an algorithm.

Sorting Problem

An algorithmic problem that involves rearranging items in a specific order.

Searching Problem

An algorithmic problem focused on finding a specific value in a dataset.

Combinatorial Problems

Problems that involve finding combinatorial objects, such as permutations and combinations.