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Data Structures and Algorithms in C
Data structures in C organize information for efficient access and updates. Common structures include arrays, stacks, queues, linked lists, trees, and graphs. Choosing the right structure for the problem improves performance and clarity when implementing algorithms in C.
A data structure defines how data is stored and accessed; an algorithm is a step-by-step method for solving a problem. Learning data structures and algorithms enables writing programs that are both time- and space-efficient.
- Abstract data types
- Order lists and arrays
- Polynomial representation using arrays
- Algorithm analysis using frequency count
- time complexity using dig O notation
- Recursive calls
- Array
- Bidirectional map
- Bit array
- Bit field, Bit board
- Bitmap
- Circular buffer
- Control table
- Dynamic array
- Hashed array tree
- Height map
- Lookup table
- Matrix
- Parallel array, Sorted array
- Sparse array
- Sparse matrix
- Life vector
- Variable-length array
- Doubly linked list
- Linked list
- Self-organizing list
- Skip list
- Unrolled linked list
- V List
- Xor linked list
- Zipper
- Doubly connected edge list
- Manipulating on singly linked list
- Insertion
- Deletion
- Copy
- Append
- Circular list
- Double linked list
- Polynomial addition using linked list
- Sparse matrix
- What is stack
- Push and pop operation of stack
- Evaluation of arithmetic expression in stack
- What is queue
- Types of queue
- Simulation using queues
- Linked list represents stack& queues
- Height
- Representation using pointer
- Recursive & Non-recursive
- Tree construction using pre-order index
- past order in-order traversal
- Relationship between internal and external nodes
- Threshed binary trees
- Binary search tree-time complexity
- insertion and retrieval
- Heaps and priority queues
- AVL trees
- B-trees
- AA tree
- AVL tree
- Binary search tree
- Binary tree
- Cartesian tree
- Randomized binary search tree
- Red-black tree, Rope
- Scapegoat tree
- Self-balancing binary search tree
- Splay tree
- T-tree
- Tango tree
- Threaded binary tree
- Top tree
- Treap
- Weight-balanced tree
- B-tree
- B+ tree
- B*-tree
- B sharp tree
- Dancing tree
- 2-3 tree
- 2-3-4 tree
- Queap
- Fusion tree
- Bx-tree
- Ternary search tree
- And or tree
- (a,b)-tree
- Link/cut tree
- SPQR-tree
- Spaghetti stack
- Disjoint-set data structure
- Fusion tree
- Enfilade
- Exponential tree
- Fenwick tree
- Van Emden Boas tree
- Segment tree
- Interval tree
- Range tree
- Implicit kd-tree
- Min/max kd-tree
- Adaptive k-d tree
- Quadtree
- Octree, Linear o-c tree
- Z-order
- R-tree, R+ tree, R* tree
- Hilbert R-tree
- X-tree
- Metric tree, Cover tree
- M-tree, VP-tree
- BK-tree
- Bounding interval hierarchy
- BSP tree
- Rapidly exploring random tree
- Syntax tree
- Abstract syntax tree
- Parse tree , decision tree
- Alternating decision tree
- Mini max tree
- Finger tree
- Insertion in array
- Deletion in array
- Reverse of array
- Traversing of array element
- Sequential and binary search
- Time complexity
- Selection and bubble sort
- Quick sort
- Merge sort
- Heap sort
- Hashing schemes
- Collision handling using linear
- quadratic probing
- Bloom filter
- Distributed hash table
- Hash array mapped tree
- Hash list
- Hash table
- Hash tree
- Prefix hash tree
- Graph operation
- Representation
- Traversal, Spanning trees
- Kruskal's algorithm for minimum cost Spanning trees
- Prim's algorithm for shortest path
- Dijkstra's algorithm for shortest path.
- Adjacency list,
- Adjacency matrix
- Graph-structured stack
- Scene graph
- Binary decision diagram
- Zero suppressed decision diagram
- And-inverter graph
- Directed graph
- Directed acyclic graph
- Propositional directed acyclic graph
- Multi graph
- Hyper graph
- Light map
- Winged edge
- Doubly connected edge list
- Quad-edge
- Routing table
- Symbol table
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