🔥 Maximum Product Subarray | LeetCode Medium | Kadane’s Algorithm Variation Explained Step-by-Step
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🔥 Maximum Product Subarray | LeetCode Medium | Kadane’s Algorithm Variation Explained Step-by-Step
In this video, we’ll solve the LeetCode problem — “Maximum Product Subarray” from our DSA Sheet. It’s a tricky variation of Kadane’s Algorithm where we have to handle positive, negative, and zero values smartly to find the subarray with the maximum product. We’ll cover: Problem Explanation Intuition & Approach Dry Run Example ...
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SOLVED: Convert the pseudocode into a C functionThe Maximum Subarray ProblemThe maximum subarray problem involves finding a contiguous part of an array of numbers that adds up to the greatest possible sum.Maximum subarray problem input: a non-empty vector V of n integersOutput: indices b, e such that 0 ≤ b sum(v[b:e]): b = i e = j return (b, e)The two nested loops together iterate O(n^2) times, and the sum operation takes O(n) time, so the total time comp
SOLVED: Convert the pseudocode into a C functionThe Maximum Subarray ProblemThe maximum subarray problem involves finding a contiguous part of an array of numbers that adds up to the greatest possible sum.Maximum subarray problem input: a non-empty vector V of n integersOutput: indices b, e such that 0 ≤ b sum(v[b:e]): b = i e = j return (b, e)The two nested loops together iterate O(n^2) times, and the sum operation takes O(n) time, so the total time comp
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