Sure! Here's a quick-reference summary of all major Data Structures with their key operations (like enqueue/dequeue for Queue). This will help you revise fast for viva or practicals:
π DSA Operation Summary Table
Data Structure | Key Operations | Explanation |
---|---|---|
Array | Insert, Delete, Traverse, Search, Update | Fixed size, indexed access |
Stack | push (top), pop (top), peek |
LIFO – Last In First Out |
Queue | enqueue (rear), dequeue (front) |
FIFO – First In First Out |
Circular Queue | enqueue (rear), dequeue (front) |
Rear and front wrap around |
Linked List (Singly) | Insert, Delete, Traverse | Dynamic size, nodes with data and next |
Doubly Linked List | Insert, Delete, Traverse (both directions) | Each node has prev , data , next |
Circular Linked List | Traverse (ends connect) | Last node points to head |
Stack using Array/LL | push/pop | LIFO using static/dynamic memory |
Queue using Array/LL | enqueue/dequeue | FIFO using static/dynamic memory |
Binary Tree | Insert, Traverse (inorder, preorder, postorder) | Tree with 2 children max per node |
BST (Binary Search Tree) | Insert, Delete, Search | Left < Root < Right |
Heap (Min/Max) | Insert, Delete root, Heapify | Complete binary tree with heap property |
Graph | Add edge, DFS, BFS | Nodes connected with edges |
Hash Table | Insert, Search, Delete | Uses hash function for indexing |
Trie | Insert, Search words | Tree-like for strings/words |
Priority Queue | insert, removeHighestPriority | Highest priority removed first |
Deque (Double-ended Queue) | insertFront, insertRear, deleteFront, deleteRear | Insert/Delete from both ends |
Matrix (2D Array) | Add, Multiply, Transpose | Used in mathematical operations |
String (as DS) | Reverse, Palindrome, Frequency | Treated as character array |
Polynomial (using LL) | Add, Multiply | Each node has coefficient & exponent |
π§ Quick Mnemonics:
-
Stack = LIFO → Last In First Out → Use
push/pop
from top -
Queue = FIFO → First In First Out → Use
enqueue
(rear),dequeue
(front) -
BST = Sorted Binary Tree → Left < Root < Right
-
Heap = Max/Min tree → Root has highest/lowest value
-
Graph → Uses edges and nodes, can be directed/undirected
Let me know if you want a printable PDF of this or code examples for each.
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