Overview
Time complexity is a fundamental concept in computer science that helps us evaluate the efficiency of algorithms. By understanding how the runtime of an algorithm grows with input size, we can make informed decisions about which algorithms to use in different scenarios. This knowledge is crucial for...
Key Terms
Example: A recipe is an algorithm for cooking.
Example: O(n) means the runtime grows linearly with input size.
Example: In a linear search, the worst-case is when the item is not found.
Example: In a linear search, the best-case is when the item is the first element.
Example: Average-case for quicksort is O(n log n).
Example: Bubble sort and quicksort are common sorting algorithms.
Related Topics
Algorithm Design
The process of defining a step-by-step solution to a problem, focusing on efficiency and effectiveness.
intermediateData Structures
The study of how data can be organized and manipulated efficiently, which is crucial for algorithm performance.
intermediateComplexity Theory
A branch of computer science that studies the inherent difficulty of computational problems and the resources needed to solve them.
advancedKey Concepts
Big O NotationAlgorithm EfficiencyWorst-case AnalysisBest-case Analysis