Big O Complexity Cheat Sheet



Java Collections Complexity cheatsheet
Below are the Big O performance of common functions of different Java Collections.
List | Add | Remove | Get | Contains | Next | Data Structure
---------------------|------|--------|------|----------|------|---------------
ArrayList | O(1) | O(n) | O(1) | O(n) | O(1) | Array
LinkedList | O(1) | O(1) | O(n) | O(n) | O(1) | Linked List
CopyOnWriteArrayList | O(n) | O(n) | O(1) | O(n) | O(1) | Array
Set | Add | Remove | Contains | Next | Size | Data Structure
----------------------|----------|----------|----------|----------|------|-------------------------
HashSet | O(1) | O(1) | O(1) | O(h/n) | O(1) | Hash Table
LinkedHashSet | O(1) | O(1) | O(1) | O(1) | O(1) | Hash Table + Linked List
EnumSet | O(1) | O(1) | O(1) | O(1) | O(1) | Bit Vector
TreeSet | O(log n) | O(log n) | O(log n) | O(log n) | O(1) | Red-black tree
CopyOnWriteArraySet | O(n) | O(n) | O(n) | O(1) | O(1) | Array
ConcurrentSkipListSet | O(log n) | O(log n) | O(log n) | O(1) | O(n) | Skip List
Queue | Offer | Peak | Poll | Remove | Size | Data Structure
------------------------|----------|------|----------|--------|------|---------------
PriorityQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
LinkedList | O(1) | O(1) | O(1) | O(1) | O(1) | Array
ArrayDequeue | O(1) | O(1) | O(1) | O(n) | O(1) | Linked List
ConcurrentLinkedQueue | O(1) | O(1) | O(1) | O(n) | O(n) | Linked List
ArrayBlockingQueue | O(1) | O(1) | O(1) | O(n) | O(1) | Array
PriorirityBlockingQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
SynchronousQueue | O(1) | O(1) | O(1) | O(n) | O(1) | None!
DelayQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
LinkedBlockingQueue | O(1) | O(1) | O(1) | O(n) | O(1) | Linked List
Map | Get | ContainsKey | Next | Data Structure
----------------------|----------|-------------|----------|-------------------------
HashMap | O(1) | O(1) | O(h / n) | Hash Table
LinkedHashMap | O(1) | O(1) | O(1) | Hash Table + Linked List
IdentityHashMap | O(1) | O(1) | O(h / n) | Array
WeakHashMap | O(1) | O(1) | O(h / n) | Hash Table
EnumMap | O(1) | O(1) | O(1) | Array
TreeMap | O(log n) | O(log n) | O(log n) | Red-black tree
ConcurrentHashMap | O(1) | O(1) | O(h / n) | Hash Tables
ConcurrentSkipListMap | O(log n) | O(log n) | O(1) | Skip List

Mar 26, 2020 The first has a time complexity of O(N) and the latter has O(1). Python Regex Cheat Sheet. Writing to an excel sheet using Python. Big-O Cheat Sheet Generated December 10, 2013. Algorithm Data Structure Time Complexity Space Complexity Average Worst Depth First Search (DFS) Graph of jVj. Big-O Algorithm Complexity Cheat Sheet Created Date: 7/10/2016 7:49:20 PM.

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commented Feb 7, 2021

You've mixed data structures between LinkedList and ArrayDequeue in the Queue section.

commented Mar 11, 2021

Do these figures still hold in the new Java versions? If not, then I would suggest adding the Java-version these performances were measured at.

I presume by and large the performance does not change dramatically though.

commented Apr 21, 2021

Big O Complexity Cheat Sheet Pdf

Do these figures still hold in the new Java versions? If not, then I would suggest adding the Java-version these performances were measured at. Ableton live.

Top macbook pro apps. I presume by and large the performance does not change dramatically though.

I highly doubt this was measured. It's probably inferred from the implementation. And I doubt the complexity of the implementations changed. Most algorithms have been around for a long time.

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Sorting Algorithms
Sorting Algorithms Space complexityTime complexity
Worst caseBest caseAverage caseWorst case
Insertion SortO(1)O(n)O(n2) O(n2)
Selection SortO(1)O(n2) O(n2) O(n2)
Smooth SortO(1)O(n)O(n log n)O(n log n)
Bubble SortO(1)O(n)O(n2) O(n2)
Shell SortO(1)O(n)O(n log n2) O(n log n2)
MergesortO(n)O(n log n)O(n log n)O(n log n)
QuicksortO(log n)O(n log n)O(n log n)O(n log n)
HeapsortO(1)O(n log n)O(n log n)O(n log n)
Big o complexity cheat sheet

Big O Time Complexity Cheat Sheet

Data Structures Comparison
Data Structures Average CaseWorst Case
SearchInsertDeleteSearchInsertDelete
ArrayO(n)N/AN/AO(n)N/AN/A
Sorted ArrayO(log n)O(n)O(n)O(log n)O(n)O(n)
Linked ListO(n)O(1)O(1)O(n)O(1)O(1)
Doubly Linked ListO(n)O(1)O(1)O(n)O(1)O(1)
StackO(n)O(1)O(1)O(n)O(1)O(1)
Hash tableO(1)O(1)O(1)O(n)O(n)O(n)
Binary Search TreeO(log n)O(log n)O(log n)O(n)O(n)O(n)
B-TreeO(log n)O(log n)O(log n)O(log n)O(log n)O(log n)
Red-Black treeO(log n)O(log n)O(log n)O(log n)O(log n)O(log n)
AVL TreeO(log n)O(log n)O(log n)O(log n)O(log n)O(log n)

Big O Complexity Cheat Sheet Download

Growth Rates
n f(n)log nnn log nn22nn!
100.003ns0.01ns0.033ns0.1ns1ns3.65ms
200.004ns0.02ns0.086ns0.4ns1ms77years
300.005ns0.03ns0.147ns0.9ns1sec8.4x1015yrs
400.005ns0.04ns0.213ns1.6ns18.3min--
500.006ns0.05ns0.282ns2.5ns13days--
1000.070.1ns0.644ns0.10ns4x1013yrs --
1,0000.010ns1.00ns9.966ns1ms----
10,0000.013ns10ns130ns100ms----
100,0000.017ns0.10ms1.67ms10sec----
1'000,0000.020ns1ms19.93ms16.7min----
10'000,0000.023ns0.01sec0.23ms1.16days----
100'000,0000.027ns0.10sec2.66sec115.7days----
1,000'000,0000.030ns1sec29.90sec31.7 years----




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