## Dynamic Programming - DP

Optimizes problem-solving through subproblem breakdown, storing solutions to enhance efficiency.

Optimizes problem-solving through subproblem breakdown, storing solutions to enhance efficiency.

Strings are sequences of characters, fundamental in programming for text representation, manipulation, and processing.

A trie is a tree-like data structure for storing and retrieving dynamic sets, often used for efficient string matching.

A stack is a linear data structure that follows the Last In, First Out (LIFO) principle for storing and retrieving elements.

Recursion is a programming technique where a function calls itself to solve smaller instances of a problem, aiding in iteration.

A queue is a linear data structure that follows the First In, First Out (FIFO) principle for storing and retrieving elements.

A linked list is a linear data structure where elements are connected via pointers, allowing dynamic memory allocation and efficient insertions.

A graph is a versatile data structure consisting of nodes and edges, representing relationships between entities in a network or system.

List of top data structure and algorithmic problems commonly asked in technical interviews.

Binary Tree: Tree data structure where each node has at most two children, left and right, facilitating efficient search and traversal.

Binary Search Tree: Binary tree with the property that for each node, values in its left subtree are less, and in the right, greater.

Arrays: Ordered, fixed-size data structures storing elements of the same type, accessed by index, crucial for efficient data manipulation.

Python: Readable, versatile, high-level language with extensive libraries for rapid development across various domains.

Java: Object-oriented, versatile language for diverse application development with simplicity, reliability, and extensive libraries.