算法复杂度这件事
这篇文章覆盖了计算机科学里面常见算法的时间和空间的大 O 复杂度。我之前在参加面试前,经常需要花费很多时间从互联网上查找各种搜索和排序算法的优劣,以便我在面试时不会被问住。最近这几年,我面试了几家硅谷的初创企业和一些更大一些的公司,如 Yahoo、eBay、LinkedIn 和 Google,每次我都需要准备这个,我就在问自己,“为什么没有人创建一个漂亮的大 O 速查表呢?”所以,为了节省大家的时间,我就创建了这个,希望你喜欢!
— Eric
图例
数据结构操作
数据结构 |
时间复杂度 |
空间复杂度 |
|
平均 |
最差 |
最差 |
|
访问 |
搜索 |
插入 |
删除 |
访问 |
搜索 |
插入 |
删除 |
|
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) |
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 |
– |
O(1) |
O(1) |
O(1) |
– |
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 |
– |
O(log(n)) |
O(log(n)) |
O(log(n)) |
– |
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 |
– |
O(log(n)) |
O(log(n)) |
O(log(n)) |
– |
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) |
数组排序算法
算法 |
时间复杂度 |
空间复杂度 |
|
最佳 |
平均 |
最差 |
最差 |
Quicksort |
O(n log(n)) |
O(n log(n)) |
O(n^2) |
O(log(n)) |
Mergesort |
O(n log(n)) |
O(n log(n)) |
O(n log(n)) |
O(n) |
Timsort |
O(n) |
O(n log(n)) |
O(n log(n)) |
O(n) |
Heapsort |
O(n log(n)) |
O(n log(n)) |
O(n log(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) |
Shell Sort |
O(n) |
O((nlog(n))^2) |
O((nlog(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) |
图操作
节点 / 边界管理 |
存储 |
增加顶点 |
增加边界 |
移除顶点 |
移除边界 |
查询 |
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|) |
堆操作
类型 |
时间复杂度 |
|
Heapify |
查找最大值 |
分离最大值 |
提升键 |
插入 |
删除 |
合并 |
Linked List (sorted) |
– |
O(1) |
O(1) |
O(n) |
O(n) |
O(1) |
O(m+n) |
Linked List (unsorted) |
– |
O(n) |
O(n) |
O(1) |
O(1) |
O(1) |
O(1) |
Binary Heap |
O(n) |
O(1) |
O(log(n)) |
O(log(n)) |
O(log(n)) |
O(log(n)) |
O(m+n) |
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) |
大 O 复杂度图表
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- Cracking the Coding Interview: 150 Programming Questions and Solutions
- Introduction to Algorithms, 3rd Edition
- Data Structures and Algorithms in Java (2nd Edition)
- High Performance JavaScript (Build Faster Web Application Interfaces)
贡献者
- Eric Rowell, creator of Concrete.js, an HTML5 Canvas Framework
- Quentin Pleple
- Michael Abed
- Nick Dizazzo
- Adam Forsyth
- David Dorfman
- Jay Engineer
- Jennifer Hamon
- Josh Davis
- Nodir Turakulov
- Bart Massey
- Vinnie Magro
- Miguel Amigot
- Drew Bailey
- Aneel Nazareth
- Rahul Chowdhury
- Robert Burke
- steven41292
- Brandon Amos
- Mike Davis
- Casper Van Gheluwe
- Joel Friedly
- Oleg
- Renfred Harper
- Piper Chester
- Eric Lefevre-Ardant
- Jonathan McElroy
- Si Pham
- mcverry
- Max Hoffmann
- Alejandro Ramirez
- Damon Davison
- Alvin Wan
- Alan Briolat
- Drew Hannay
- Andrew Rasmussen
- Dennis Tsang
- Bahador Saket
原创文章,作者:kepupublish,如若转载,请注明出处:https://blog.ytso.com/41799.html