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Complexities

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This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science. When preparing for technical interviews in the past, I found myself spending hours crawling the internet putting together the best, average, and worst case complexities for search and sorting algorithms so that I wouldn’t be stumped when asked about them.

VisuAlgo.net. visualising data structures and algorithms through animation

Big-O Complexity Chart

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Common Data Structure Operations

Data Structure Time Complexity Space Complexity
Average Worst Worst
Access Search Insertion Deletion Access Search Insertion Deletion
Array O(1) O(n) O(n) O(n) O(1) O(n) O(n) O(n) O(n)
Stack O(n) O(n) O(1) O(1) O(n) O(n) O(1) O(1) O(n)
Queue O(n) O(n) O(1) O(1) O(n) O(n) O(1) O(1) O(n)
Singly-Linked List O(n) O(n) O(1) O(1) O(n) O(n) O(1) O(1) O(n)
Doubly-Linked List O(n) O(n) O(1) O(1) O(n) O(n) O(1) O(1) O(n)
Skip List O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n) O(n) O(n) O(n) O(n log(n))
Hash Table N/A O(1) O(1) O(1) N/A O(n) O(n) O(n) O(n)
Binary Search Tree O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n) O(n) O(n) O(n) O(n)
Cartesian Tree N/A O(log(n)) O(log(n)) O(log(n)) N/A O(n) O(n) O(n) O(n)
B-Tree O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n)
Red-Black Tree O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n)
Splay Tree N/A O(log(n)) O(log(n)) O(log(n)) N/A O(log(n)) O(log(n)) O(log(n)) O(n)
AVL Tree O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n)
KD Tree O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(n) O(n) O(n) O(n) O(n)

Array Sorting Algorithms

Algorithm Time Complexity Space Complexity
Best Average Worst Worst
Quicksort O(n log(n)) O(n log(n)) O(n^2) O(log(n))
Mergesort O(nlog(n)) O(nlog(n)) O(nlog(n)) O(n)
Timsort O(n) O(nlog(n)) O(nlog(n)) O(n)
Heapsort O(nlog(n)) O(nlog(n)) O(nlog(n)) O(1)
Bubble Sort O(n) O(n^2) O(n^2) O(1)
Insertion Sort O(n) O(n^2) O(n^2) O(1)
Selection Sort O(n^2) O(n^2) O(n^2) O(1)
Tree Sort O(n log(n)) O(n log(n)) O(n^2) O(n)
Shell Sort O(n log(n)) O(n(log(n))^2) O(n(log(n))^2) O(1)
Bucket Sort O(n+k) O(n+k) O(n^2) O(n)
Radix Sort O(nk) O(nk) O(nk) O(n+k)
Counting Sort O(n+k) O(n+k) O(n+k) O(k)
Cubesort O(n) O(n log(n)) O(n log(n)) O(n)

Graph Data Structure Operations

Data Structure Time Complexity
Storage Add Vertex Add Edge Remove Vertex Remove Edge Query
Adjacency list O(|V|+|E|) O(1) O(1) O(|V| + |E|) O(|E|) O(|V|)
Incidence list O(|V|+|E|) O(1) O(1) O(|E|) O(|E|) O(|E|)
Adjacency matrix O(|V|^2) O(|V|^2) O(1) O(|V|^2) O(1) O(1)
Incidence matrix O(|V| ? |E|) O(|V| ? |E|) O(|V| ? |E|) O(|V| ? |E|) O(|V| ? |E|) O(|E|)

Heap Data Structure Operations

Data Structure Time Complexity
Find Max Extract Max Increase Key Insert Delete Merge
Binary Heap O(1) O(log(n)) O(log(n)) O(log(n)) O(log(n)) O(m+n)
Pairing Heap O(1) O(log(n)) O(log(n)) O(1) O(log(n)) O(1)
Binomial Heap O(1) O(log(n)) O(log(n)) O(1) O(log(n)) O(log(n))
Fibonacci Heap O(1) O(log(n)) O(1) O(1) O(log(n)) O(1)

Graph Algorithms

Algorithm Time Complexity Space Complexity
Average Worst Worst
Dijkstra’s algorithm O(|E| log |V|) O(|V|^2) O(|V| + |E|)
A* search algorithm O(|E|) O(b^d) O(b^d)
Prim’s algorithm O(|E| log |V|) O(|V|^2) O(|V| + |E|)
Bellman–Ford algorithm O(|E| ? |V|) O(|E| ? |V|) O(|V|)
Floyd-Warshall algorithm O(|V|^3) O(|V|^3) O(|V|^2)
Topological sort O(|V| + |E|) O(|V| + |E|) O(|V| + |E|

Complexities

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原文地址:http://blog.csdn.net/songzitea/article/details/52154174

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