One Pager Cheat Sheet

• We're going to learn about Kadane's Algorithm and its implementation in Python, JavaScript, and Java, in order to solve the Maximum Subarray Problem.
• Kadane's Algorithm is a form of Dynamic Programming developed by Joseph Born Kadane which provides an optimal solution for the Maximum Subarray Problem.
• The Maximum Subarray Problem is to find the largest sum of a contiguous subarray in an input array of size n.
• The Brute Force approach can be used to calculate the largest sum of a contiguous subarray in an array by comparing all possible subarrays and setting the max sum to a globalMaxSum variable, with a time complexity of O(n^2).
• The time complexity of this algorithm is O(n²), as it requires two loops (outer loop with index i from 0 to n-1 and inner loop with index j from j set to i to n-1).
• Kadene's Algorithm is an optimal approach with time complexity O(n), to the maximum subarray problem which is found by looping through the array, comparing the local Max Sums, and updating the global Max Sum at each iteration.
• Kadene's Algorithm to find the largest sum of a contiguous subarray has a time complexity of O(n) due to its single loop iteration from index 0 to index n-1.
• We solved the Maximum Subarray Problem in an optimal way using Kadene's Algorithm.