Blind 75 LeetCode Questions: Ace Algorithms Coding Interview

Demonstrates solving the best time to buy and sell stock by contrasting naive O(n^2) loops with an efficient O(n) single-pass approach using a running minimum price and max profit.

Detect duplicates in an array of integers using brute-force pairs, then sorting, and finally a hash set to achieve linear time with linear space.

Solve the product of array except self without division by using prefix and suffix products, building a prefix array and a suffix variable for linear time.

Master the maximum subarray problem by tracking a current sum and a running maximum with two variables, achieving linear time and constant space.

Learn to compute the maximum product subarray by tracking minimum and maximum products at each step, resetting on zero, with an O(n) time, O(1) space Java solution.

Find the minimum in a rotated sorted array using a modified binary search that locates the decreasing point with left, right, and mid pointers, delivering logarithmic time and constant space.

Learn to search a rotated sorted array with a modified binary search, identifying the sorted half and adjusting pointers to locate the target in logarithmic time.

Sort the input and use a two-pointer approach to find all unique triplets that sum to zero, iterating with the first element and skipping duplicates, achieving O(n^2) time.

Solve container with most water using a two-pointer approach, moving the shorter height, computing area as the minimum height times distance, updating the max water, O(n) time and O(1) space.

Explore how to add two integers without arithmetic operators using bitwise xor and, left shift carry, iterating until no carry remains; handle negative numbers via two's complement.

Count the number of one bits in a 32-bit integer's binary representation using a shifting mask and bitwise and, by testing each bit.

Learn to compute the number of one bits from 0 to n with a dynamic programming approach using an offset to powers of two, achieving O(n) time and space.

Solve the missing number problem by identifying the absent integer in 0..n from a given array, comparing a naive set approach with a constant-space xor method implemented in Java.

Reverse the 32-bit binary representation of an integer using left shifts, right shifts, and bitwise operations to build and return the reversed value.

Learn to count ways to climb n stairs with 1 or 2 steps using top-down and bottom-up dynamic programming, reveal the fibonacci pattern, and optimize to constant space.

Use a bottom-up dynamic programming approach to solve coin change with infinite coin supply, building a dp table of length amount+1 to minimize the number of coins.

Compute the length of the longest increasing subsequence in an array of integers using a bottom-up dynamic programming approach with a DP table, achieving O(n^2) time and O(n) space.

solve the longest common subsequence problem using bottom-up dynamic programming, building an (m+1) by (n+1) table to compute the LCS length with time and space complexity O(mn).

Explore the word break problem using bottom-up dynamic programming on a dictionary to determine if the string can be constructed, returning true or false.

Solve the combination sum iv problem with a bottom-up dynamic programming approach using a one-dimensional tabulation table of length target plus one, with dp[0] = 1.

Solve the house robber problem by selecting non-adjacent houses to maximize money using dynamic programming. The lecture demonstrates a dynamic programming table and a constant-space optimization using two variables.

Solve the circular house robber II problem by applying the house robber algorithm to two subarrays, zero to n-2, and one to n-1, and take the max.

Decode ways uses dynamic programming to count how many ways a digit string maps to letters (1-26), handling zeros and valid pairs, as 226 yields 3 and 706 yields 0.

Learn to solve the unique paths problem on an m by n grid with dynamic programming, moving only right or down. Implement a Java solution with time and space O(mn).

Solve the jump game on an array of integers by tracking the farthest reachable index to decide if the last index is reachable with a linear time, constant space solution.

Clone a graph using BFS on an adjacency list, cloning nodes via a hashmap and a queue, preserving edges between node neighbors.

Learn to solve the course schedule problem using topological sorting with Kahn's algorithm, building an adjacency list, computing indegrees from prerequisites, and validating that all courses can be enrolled.

Solve the pacific atlantic water flow problem on an n by n grid. Apply boundary scanning with depth-first search to mark pacific and atlantic reachability and extract common cells.

Solve number of islands problem on a binary grid with DFS. Traverse connected ones horizontally or vertically, updating visited lands to zero in place, and count islands as you go.

Learn to solve the longest consecutive sequence problem in linear time with a hash set, identifying starts and extending with a while loop to achieve O(n) time and O(n) space.

Derive the alien language letter order by building a precedence graph from sorted words and applying Kahan's topological sort to return the order or an empty string.

Use union-find to solve graph valid tree: track roots with find and union, detect cycles, and ensure a single connected component among n nodes with given undirected edges.

Solve the number of connected components in an undirected graph using the union find algorithm, maintaining root and rank arrays and performing find and union operations.

Learn to insert an interval into a sorted, non-overlapping list by start time, and merge overlaps to form a single merged interval; it runs in O(n) time with O(1) space.

Sort the intervals by start time, then merge overlapping intervals to produce a merged list of intervals.

Sort the intervals by end time and use a two-pointer approach to count non-overlapping intervals, then return the number of removals as the total minus non-overlapping.

Solve the meeting rooms problem by sorting intervals by start time and comparing end and next start to detect overlaps, determining if all meetings can be attended.

Learn to solve the Meeting Rooms II problem by sorting intervals by start times, using a min-heap to track end times, and determine the minimum number of rooms.

Learn to reverse a singly linked list by four approaches: naive stack-based, iterative with prev, curr, and temp pointers, and two recursive methods, returning the reversed head.

Detect cycles in a linked list using a set, then optimize with slow and fast pointers to determine true or false.

Merge two sorted lists by splicing nodes from two sorted linked lists using two pointers with a fake head. Achieve O(m+n) time and constant space by not recreating nodes.

Divide and conquer merges k sorted lists by pairwise merging with doubling intervals, producing a single sorted list in O(n log k) time and O(1) space using two-list merges.

Remove the nth node from the end of a linked list using a dummy head, illustrating a two-pass approach and a single-pass method with o(n) time and o(1) space.

Partition the linked list with slow and fast pointers to middle. Reverse the second half and merge with the first using a dummy node for linear time, constant space.

Solve the set matrix zeros problem in place with constant space by using first row and column flags, pre-processing, and then nullifying affected rows and columns in O(mn) time.

Discover how to perform spiral order traversal of a matrix using four pointers, traversing top row, right column, bottom row, and left column, with boundary checks to avoid duplicates.

Rotate a square matrix 90 degrees clockwise by flipping on secondary diagonal and horizontally, or perform an in-place layer-by-layer rotation using four pointers left, right, top, bottom in O(M) time.

Learn an in-place method to rotate a square matrix 90 degrees clockwise by transposing over the main diagonal and reversing rows, with O(n^2) time and O(1) space.

Perform a depth-first search to determine if the word exists on the board by exploring top, left, bottom, and right from each cell, with visited tracking and backtracking.

Develop a linear-time solution to the longest substring without repeating characters using a sliding window with a hash map to track indices, updating the left pointer and the best length.

Learn to solve the longest substring with at most k replacements using a sliding window and a 26-letter frequency array, tracking max frequency to achieve linear time and constant space.

Master the minimum window substring using two hash maps and the two-pointer approach to build a valid window containing all characters of the target, then return the smallest window.

Determine if two strings are valid anagrams by comparing character counts, first with a hash map and then with a 26-length array for constant space, using lowercase letters.

Group anagrams by sorting each string to a key, storing strings in a hash map, and returning the grouped anagrams as a list of lists.

Learn to determine valid parentheses by using a stack and a hash map to match opening and closing brackets across (), [], and {}, in linear time and space.

Solve the valid palindrome problem by using a two-pointer approach that considers only alphanumeric characters and ignores case, achieving O(n) time and O(1) space.

Learn to find the longest palindromic substring by expanding around centers, achieving quadratic time with constant extra space and understanding the key palindrome concepts for coding interviews.

Count palindromic substrings by center expansion around each character and between characters, handling odd and even lengths, with O(n^2) time and O(1) space.

Encode a list of strings into one string using length prefixes and a hash, then decode to recover the original list with two pointers.

Use DFS to compute the maximum depth of a binary tree. Return 1 plus max(left, right) and use null base case 0; analyze O(n) time and space.

Compare two binary trees to determine if they are identical by recursively checking root values and corresponding left and right subtrees using a depth-first search.

Learn how to invert a binary tree by recursively flipping left and right subtrees and swapping children, achieving the inverted tree with linear time and space complexity.

Solve the binary tree maximum path sum with a depth-first search tracking a global max. Consider paths through any node, including the root, using zero for nulls.

Perform a binary tree level order traversal using a queue to process each level, returning a list of level-wise node values with O(n) time and space.

Serialize a binary tree to a string via preorder traversal, then deserialize it back using a queue and DFS, with nulls represented by a hash, in O(n) time and space.

Solve the subtree of another binary tree problem using a dfs approach and a helper to compare subtrees, returning true or false with time complexity o(mn) and space o(m).

Construct a binary tree from preorder and inorder traversal using a recursive approach, identifying root nodes and partitioning left and right subtrees with a hashmap for constant-time index lookup.

Solve the binary search tree validation problem using inorder traversal; verify left values are less than root and right values are greater, with an iterative stack-based approach.

Explore through a BST, find the kth smallest element using in-order traversal, and compare naive sorting with an efficient iterative stack approach.

Find the lowest common ancestor in a binary search tree by comparing two nodes, using a min and max approach to navigate left or right and return the ancestor.

Implement a trie (prefix tree) with insert, search, and start with operations using a hash map of children and an is_end flag to mark word endings.

Build a trie-based data structure that supports addWord and searchWord with dot wildcard matching and end-of-word markers.

Build a trie from the given words and perform a dfs on the board to identify and return the words that exist, marking visited cells to avoid duplicates.