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LeetCode The Hard Way Solutions

website·Indexed 32 days ago

https://leetcodethehardway.com/

A collection of solutions for LeetCode problems across various difficulty levels (Easy, Medium, Hard), organized by problem number.

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What's inside LeetCode The Hard Way

  1. Overview of LeetCode The Hard Way learning resources

    LeetCode The Hard Way provides a structured approach to mastering data structures and algorithms through four primary resource types:

    • Tutorials: Conceptual learning for data structures, algorithms, math, strings, graph theory, and other core topics.
    • Roadmaps: Curated problem sets and focused practice paths for specific topics and study plans.
    • Solution Catalog: Detailed explanations for individual LeetCode problems, organized by problem ID ranges.
    • Templates: Reusable implementation templates for common algorithm patterns to accelerate coding.

  2. Overview of Cyclic Sort algorithm

    Cyclic Sort is an in-place, unstable comparison sort algorithm that is theoretically optimal regarding the total number of writes to the original array. It works by factoring the permutation to be sorted into several cycles, which are individually rotated to achieve the sorted result. It is particularly effective for problems involving arrays containing numbers in a known range, such as finding missing or duplicate numbers.

  3. Overview of the Two Pointers technique

    The Two Pointers technique is used to iterate through a data set (typically an array or list) in a controlled way to achieve linear time complexity, often outperforming brute-force approaches. It typically involves initializing one pointer at the beginning and another at the end of the data set, moving them toward each other based on specific conditions. This is effective for searching for pairs in sorted arrays, pattern matching, and data analysis.

  4. Overview of the Sliding Window technique

    Sliding Window is an algorithmic technique used to iterate through a finite data set (typically an array or string) by creating a subset (the 'window') that slides across the larger data set. This approach is used to perform specific operations on each subset, such as finding patterns, trends, maximum/minimum values, or counting occurrences. It is particularly effective for problems involving contiguous sequences, such as finding the longest substring without repeating characters or the maximum sum of a sub-array of a specific size.

  5. Overview of Manacher's Algorithm

    Manacher's algorithm is a linear time $O(n)$ algorithm used to find all palindromic substrings in a given string. It is most commonly used to find the longest palindromic substring. The algorithm exploits the symmetry of palindromes to avoid redundant calculations by using the known palindromic lengths of mirrored indices relative to a center.

  6. Overview of Hash Map (Hash Table) data structure

    A Hash Map (or hash table) is a data structure that stores key-value pairs. It uses a hash function to map keys to specific indices (hash codes) in an array of buckets, allowing for highly efficient data retrieval.

    Key characteristics include:

    • Time Complexity: Average O(1) for insertion, retrieval, and removal.
    • Flexibility: Supports various data types as keys (unlike arrays which typically require integer indices).
    • Dynamic Scaling: Can be resized to adapt to changing data volumes.
    • Collision Handling: When two keys hash to the same index, strategies like chaining or open addressing are used to resolve the conflict.

  7. Overview of Matrix Exponentiation

    Matrix exponentiation is a technique used to find the nth term of a linear recurrence with constant coefficients in O(log n) time. It applies the principle of Binary Exponentiation to matrices.

    Key mathematical properties used:

    1. Matrix Multiplication is associative: A · (B · C) = (A · B) · C.
    2. A matrix A of order (n × m) can only be multiplied by a matrix of order (m × p).
    3. Matrix multiplication of two (n × n) matrices takes O(n³) time.

  8. Understand the Bellman-Ford Algorithm for shortest paths

    The Bellman-Ford algorithm computes the shortest paths from a single source vertex to all other vertices in a weighted directed graph (digraph). Unlike Dijkstra's algorithm, which greedily selects the closest vertex using a priority queue, Bellman-Ford relaxes all edges in the graph. It performs this relaxation process $|V| - 1$ times, where $|V|$ is the number of vertices. This is based on the principle that in a graph without negative weight cycles, the shortest path between any two vertices contains at most $|V| - 1$ edges.

  10. Find the longest square streak in an array

    A square streak is a subsequence of at least length 2 where, after sorting, each element (except the first) is the square of the previous element. Given an integer array nums, the goal is to find the length of the longest such streak, returning -1 if no streak of length 2 or more exists.

    Constraints:

    • Array length: 2 <= nums.length <= 10^5
    • Element values: 2 <= nums[i] <= 10^5

  11. Determine if an array is monotonic

    An array is considered monotonic if it is either monotone increasing (for all i <= j, nums[i] <= nums[j]) or monotone decreasing (for all i <= j, nums[i] >= nums[j]). Given an integer array nums, the goal is to return true if the array satisfies either condition, and false otherwise.

  12. Determine if a number is a 'Happy Number'

    A happy number is a positive integer that eventually reaches 1 when replaced by the sum of the squares of its digits repeatedly. If the process enters a cycle that does not include 1, the number is not happy. The input constraint for the number n is 1 <= n <= 2^31 - 1.