Programming/Algorithms

From etwiki
Jump to navigation Jump to search

Pseudocode

Binary Tree Search

Iterative-Tree-Search(x, key)
   while x ≠ NIL and key ≠ x.key then
     if key < x.key then
       x := x.left
     else
       x := x.right
     end if
   repeat
   return x

Source

DFS

procedure DFS(G, v) is
    label v as discovered
    for all directed edges from v to w that are in G.adjacentEdges(v) do
        if vertex w is not labeled as discovered then
            recursively call DFS(G, w)
procedure DFS_iterative(G, v) is
    let S be a stack
    S.push(v)
    while S is not empty do
        v = S.pop()
        if v is not labeled as discovered then
            label v as discovered
            for all edges from v to w in G.adjacentEdges(v) do 
                S.push(w)

Source

Big O Notation

Adapted from Big-O Cheat Sheet
Data Structure Operations
Data Structure Time Complexity Space Complexity Notes
Average -> Worst
Access Search Insertion Deletion
Array Θ(1) -> O(1) Θ(n) -> O(n) Θ(n) -> O(n) Θ(n) -> O(n) O(n)
Stack Θ(n) -> O(n) Θ(n) -> O(n) Θ(1) -> O(n) Θ(1) -> O(n) O(n)
Queue Θ(n) -> O(n) Θ(n) -> O(n) Θ(1) -> O(n) Θ(1) -> O(n) O(n)
Linked List Θ(n) -> O(n) Θ(n) -> O(n) Θ(1) -> O(n) Θ(1) -> O(n) O(n)
Double Linked List Θ(n) -> O(n) Θ(n) -> O(n) Θ(1) -> O(n) Θ(1) -> O(n) O(n)
Hash Table N/A Θ(1) -> O(n) Θ(1) -> O(n) Θ(1) -> O(n) O(n)
Binary Search Tree Θ(log(n)) -> O(n) Θ(log(n)) -> O(n) Θ(log(n)) -> O(n) Θ(log(n)) -> O(n) O(n)
B Tree Θ(log(n)) -> O(log(n)) Θ(log(n)) -> O(log(n)) Θ(log(n)) -> O(log(n)) Θ(log(n)) -> O(log(n)) O(n) Self-balancing
Array Sorting Algorithms
Data Structure Time Complexity Space Complexity Notes
Best Average Worst
Bubble Sort Ω(n) Θ(n^2) O(n^2) O(1)
Quicksort Ω(n log(n)) Θ(n log(n)) O(n^2) O(log(n))
Mergesort Ω(n log(n)) Θ(n log(n)) O(n log(n)) O(n)
Insertion Sort Ω(n) Θ(n^2) O(n^2) O(1)
Timsort Ω(n) Θ(n log(n)) O(n log(n)) O(n) Combination of Mergesort and Insertion Sort made for Python
Heapsort Ω(n log(n)) Θ(n log(n)) O(n log(n)) O(1)
Tree Traversing Algorithms
Data Structure Time Complexity Space Complexity Notes
Best Average Worst
BFS O(V + E) = O(b^d) O(V) = O(b^d)
DFS O(b^d) O(E) = O(bd)
DFS, recursive O(V + E) O(V)