Roadmap via https://neetcode.io/roadmap
About
- Basics of arrays and how to manipulate them.
- Introduction to hashing and its applications for fast data retrieval.
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Real-life Example : In a database, hashing is used to create indexes for quick data retrieval based on a certain key. This improves the efficiency of searching for records.
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Usage Example : Given an array of integers, find two numbers such that they add up to a specific target. You can use hashing to efficiently check if the complement of the current number exists in the array.
About
- Understanding the stack data structure and its applications.
- Implementing a stack and solving problems using it.
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Real-life Example : A stack is often used to keep track of user actions, allowing them to undo operations step by step.
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Usage Example : Implement a function to check if a given string of parentheses is balanced. You can use a stack to keep track of the opening and closing brackets.
About
- Techniques involving two pointers to solve problems efficiently.
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Real-life Example : Two pointers can be used to efficiently track the positions of two vehicles in a fleet, optimizing routes and reducing travel time.
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Usage Example : Given a sorted array, find two numbers that sum to a specific target. Use two pointers starting from both ends, moving towards the center to efficiently find the pair.
About
- Understanding the binary search algorithm and its applications.
- Solving problems related to searching and optimization using binary search.
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Real-life Example : When looking for a contact in a sorted phonebook, binary search can be applied to quickly locate the contact's position.
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Usage Example : Given a sorted array, implement a function to perform binary search to find the index of a target element.
About
- Introduction to the sliding window technique for efficiently processing arrays or lists.
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Real-life Example : When analyzing temperature trends over a period, a sliding window can be used to efficiently compute average temperatures and identify patterns.
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Usage Example : Find the maximum sum of a subarray of a fixed size k in a given array. Use the sliding window technique to efficiently compute the sum as you move through the array.
About
- Basics of linked lists, types, and operations.
- Solving problems related to linked lists.
- Real-life Example : Each car is a node in a linked list, and operations like adding or removing a car are efficiently handled by updating the links.
- Usage Example : Implement a function to reverse a linked list. Traverse the list, reversing the links between nodes.
About
- Understanding tree data structures (binary trees, binary search trees, etc.).
- Tree traversal algorithms and related problem-solving.
- Real-life Example : In a company, a tree structure can represent the organizational hierarchy, with each node representing an employee and their position in the company.
- Usage Example : Given a binary tree, implement a function to perform an in-order traversal, printing the values of nodes in ascending order.
About
- Understanding trie data structures and their applications, especially in string-related problems.
- Real-life Example : Tries are commonly used to store and efficiently retrieve word suggestions in autocomplete features, like those in search engines or messaging applications.
- Usage Example : Implement a spell-checker using a trie to efficiently check if a given word is in the dictionary.
About
- Introduction to backtracking and solving problems with recursive algorithms.
- Real-life Example : Backtracking is often employed to solve complex puzzles like Sudoku, exploring different possibilities until a solution is found.
- Usage Example : Solve the N-Queens problem where you need to place N queens on an N×N chessboard such that no two queens threaten each other.
About
- Basics of graphs, types, and representations.
- Graph traversal algorithms (DFS, BFS) and problem-solving.
- Real-life Example : Graphs model relationships, and social networks use graph algorithms to find connections, recommend friends, and analyze the structure of the network.
- Usage Example : Find the shortest path between two nodes in a weighted graph. Use Dijkstra's algorithm to efficiently find the shortest path.
About
- Introduction to dynamic programming with problems involving a single dimension.
- Real-life Example : Dynamic programming can be used to find the best time to buy or sell stocks, maximizing profit over time.
- Usage Example : Given an array of integers, find the maximum subarray sum using dynamic programming to keep track of the maximum sum.
About
- Understanding the heap data structure and its applications.
- Solving problems efficiently using priority queues.
- Real-life Example : Priority queues can be used to efficiently schedule tasks based on their priority, ensuring that higher-priority tasks are executed first.
- Usage Example : Implement a priority queue to efficiently find and process the maximum or minimum element in a collection.
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- Handling problems involving intervals in data.
- Real-life Example : When scheduling appointments or events, intervals can be used to represent time slots and identify overlapping or available time periods.
- Usage Example : Given a collection of intervals, merge overlapping intervals to simplify the representation.
About
- Understanding greedy algorithms and solving problems using them.
- Real-life Example : Greedy algorithms are used in data compression, like Huffman coding, where the most frequent symbols are assigned shorter codes to optimize overall compression.
- Usage Example : Implement a function to make change using the fewest coins, selecting the largest coin denomination at each step.
About
- Advanced graph algorithms (Dijkstra's, Bellman-Ford, etc.).
- Solving complex graph problems.
- Real-life Example : Advanced graph algorithms are used to find the shortest and fastest routes in navigation systems, considering real-time traffic conditions.
- Usage Example : Solve the minimum spanning tree problem using Kruskal's algorithm.
About
- Extending dynamic programming to problems involving two dimensions.
- Real-life Example : Dynamic programming is applied to compare and match patterns in images, contributing to image recognition and computer vision.
- Usage Example : Solve the longest common subsequence problem between two strings using dynamic programming.
About
- Understanding bitwise operations and solving problems using bit manipulation.
- Real-life Example : Bit manipulation is often used in the implementation of network protocols to efficiently encode and decode data.
- Usage Example : Swap two numbers without using a temporary variable using bitwise XOR operations.
About
- Applying mathematical and geometric concepts to problem-solving.
- Real-life Example : Math and geometry are fundamental in computer graphics for tasks like rendering 3D scenes, transforming objects, and calculating lighting effects.
- Usage Example : Implement a function to check if three points in a 2D plane are collinear, using cross-product or slope comparisons.