Data Structures and Algorithms in C++ For Coding Interview

Explore the two sum problem: find two numbers that add to a target, return their indices with distinct elements, and learn the naïve O(n^2) double-loop solution with examples.

Implement the O(n^2) naive two-sum solution in C++, iterating i and j, ensuring i and j are different, and returning the pair of indices that sum to the target.

Develop the O(n log n) solution for the target-sum problem using a sorted array and a two-pointer approach, detailing how i and j move to converge on the target.

Sort the numbers with their original indices using a pair, then apply a two-pointer scan to find two values that sum to the target, returning their original indices.

Explain problem of finding maximum consecutive ones in a binary array, using example 1 1 0 1 1 1, and compare the naive approach with the optimized version.

The lecture presents a naive O(n^2) solution to the maximum consecutive ones problem, counting consecutive ones from each start index in a binary array and outlining pseudocode.

Implement the O(n^2) naive solution in C++, initializing max and current lengths, counting consecutive ones in nums, updating the maximum, and validating an accepted submission.

Introduce the O(n) solution idea and optimizations to compute the longest run of ones, using a single pass with a moving i and r and a global max length variable.

Learn to implement the O(n) solution using a two-pointer approach, where left and right pointers expand and update the current and maximum lengths in a single pass.

Identify the maximum product of any three numbers in a given integer array (length up to 10^4) and output that product, ensuring it fits in a 32-bit integer.

Explore a naive approach to maximize the product of three numbers by checking all triplets with three nested loops, detailing its O(n^3) complexity and preparing for optimization.

Sort the array to achieve an O(n log n) solution for maximizing the product of three numbers, handling negatives by using the largest three or two smallest with the largest.

Implement an O(n log n) maximum product solution in C++, sorting nums, computing P1 and P2, then returning their maximum.

Optimize the algorithm to O(n) by tracking the three largest and two smallest numbers to compute P1 and P2, avoiding full sorting.

Implement an O(n) solution that tracks the three largest and two smallest numbers, computes two product candidates, and returns their maximum.

Explore the problem of valid parentheses by analyzing a string containing open and close parentheses, curly brackets, and brackets to determine balance, and compare recursive quadratic-time and linear-time stack-based solutions.

Examine two common but flawed approaches to balancing parentheses, illustrate counterexamples, and set the stage for correct recursive and stack-based solutions to the problem.

Explore a recursive algorithm for the valid parentheses problem that runs in O(n^2) time, using removal of open-close pairs to test balance and returning true for empty strings.

Implement an O(n^2) recursive algorithm in C++ that validates strings with parentheses, braces, and brackets by finding and removing matching pairs until the string is empty.

Explore a stack-based, O(n) solution for balancing parentheses, illustrating the intuition from the recursive approach by removing inner substrings first and balancing outward.

Implement an O(n) solution for the valid parentheses problem using a stack in C++. Check base cases, push openings, pop on matches, and ensure the stack ends empty.

Learn how to compute scores in a baseball game point recorder using integers to add points, plus, D, and C operations on past rounds, with totals 30 and 27.

Explore a naive O(n^2) solution using a boolean cancelled array to process scoring operations: C cancels a previous, D doubles, and + sums two previous values, with final aggregation.

Implement the naïve O(n^2) solution by simulating operations with a cancel vector, handling C, D, and +, and converting strings to ints to compute the final sum.

The lecture presents a stack-based O(n) solution for computing scores, using push, pop, and top to manage valid scores with C canceling, D doubling, and + summing.

Implement the stack-based fence solution in c++ to process c, d, and + operations, convert numeric strings to integers, and sum the final scores from the stack.

Learn the contains duplicate II problem: find two equal numbers with index distance at most k, using a naive quadratic approach and a hash map solution for linear time.

Explore the brute-force solution for contains nearby duplicates, checking elements within k distance. The method runs in O(nk) time, sometimes O(n^2) worst case, with a hash-map O(n) solution to follow.

Implement a brute force solution for the netcode problem, using a while loop to detect duplicates within k by comparing distances. The video highlights time limit exceeded on large inputs.

Explore how to use a hash map to achieve an average-case O(n) solution for detecting nearby duplicates within distance k, with insert and update operations and hashing concepts.

implement the O(n) solution using an unordered_map to map values to their latest indices, returning true when a nearby duplicate within k is found, otherwise updating the map.