WEEK 2 Foundations of Algorithm Analysis

This set of flashcards covers essential vocabulary related to algorithms and their analysis, focusing on definitions and key concepts.

Algorithm

A step-by-step procedure for solving a problem or performing a task.

Running Time

The amount of time an algorithm takes to process input data.

Pseudo-Code

A high-level description of an algorithm that uses the conventions of programming languages but is intended for human reading.

Asymptotic Analysis

A method for describing the efficiency of an algorithm in terms of input size without implementing or running it.

Big-O Notation

A mathematical notation used to describe the upper limit of an algorithm's running time or space requirement based on the size of the input.

Primitive Operations

Basic computations performed by an algorithm, such as assignments or comparisons.

Best Case, Worst Case, Average Case

Different scenarios used to describe the efficiency of an algorithm based on various input conditions.

Time Complexity

A computational complexity that describes the amount of computational time that an algorithm takes to complete as a function of the size of the input.

Control Statements

Programming constructs that control the flow of execution (e.g. if, for, while) within an algorithm.

Input Size

The amount of data provided to an algorithm for processing.