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Data Structures and Algorithms Solutions

In this section, you will learn about the solutions of the problems of Data Structures and Algorithms.

Data Structures​

  • Array: Array is a collection of elements of the same type placed in contiguous memory locations that can be individually referenced by adding an index to a unique identifier.
  • String: A string is a sequence of characters.
  • Linked List: A linked list is a linear data structure, in which the elements are not stored at contiguous memory locations.
  • Stack: A stack is a linear data structure that follows the Last In First Out (LIFO) principle.
  • Queue: A queue is a linear data structure that follows the First In First Out (FIFO) principle.
  • Tree: A tree is a non-linear data structure that is used to store data in a hierarchical manner.
  • Graph: A graph is a non-linear data structure that consists of a finite set of vertices and edges.
  • Hashing: Hashing is a technique that is used to uniquely identify a specific object from a group of similar objects.
  • Heap: A heap is a complete binary tree that satisfies the heap property.
  • Trie: A trie is a tree-like data structure that is used to store a dynamic set of strings.

Algorithms​

  • Searching: Searching is the process of finding a specific element in a collection of elements.
  • Sorting: Sorting is the process of arranging the elements of a collection in a specific order.
  • Recursion: Recursion is a technique in which a function calls itself to solve a smaller instance of the same problem.
  • Dynamic Programming: Dynamic Programming is a technique used to solve problems by breaking them down into smaller subproblems.
  • Greedy Algorithms: Greedy Algorithms are algorithms that make a series of choices that are locally optimal at each step.
  • Backtracking: Backtracking is a technique used to solve problems by making a series of choices and backtracking when a choice leads to a dead end.
  • Divide and Conquer: Divide and Conquer is a technique used to solve problems by breaking them down into smaller subproblems, solving the subproblems, and combining the solutions to solve the original problem.
  • Bit Manipulation: Bit Manipulation is the act of algorithmically manipulating bits or binary digits.
  • Graph Algorithms: Graph Algorithms are algorithms that operate on graphs to solve problems.
  • Mathematical Algorithms: Mathematical Algorithms are algorithms that solve mathematical problems.
  • String Algorithms: String Algorithms are algorithms that operate on strings to solve problems.

Problems​

  • LeetCode: LeetCode is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • HackerRank: HackerRank is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • Codeforces: Codeforces is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • CodeChef: CodeChef is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • AtCoder: AtCoder is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • TopCoder: TopCoder is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • InterviewBit: InterviewBit is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • GeeksforGeeks: GeeksforGeeks is a platform that provides a collection of coding problems to practice and improve your coding skills.
  • Project Euler: Project Euler is a platform that provides a collection of mathematical problems to practice and improve your mathematical skills.

Resources​

  • Books: Books are a great way to learn about Data Structures and Algorithms.