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Amazon OA Coding Questions 2025
Summary
Interviewed for Amazon SDE 1 role. Faced two challenging coding problems during OA. First problem involved finding minimum cost to convert all products to variant A with specific operations. Second problem required minimizing inconvenience in a grid by strategically placing a new delivery center. Both problems required advanced algorithmic thinking and efficient solution strategies.
Full Experience
Recently completed Amazon's Online Assessment for the SDE 1 position. The OA consisted of two complex coding problems that tested both algorithmic knowledge and problem-solving skills. The first problem, Minimum Cost to Convert Products, required determining the optimal way to convert all elements in an array to 0 with specific operations, balancing cost and efficiency. The second problem, Minimize Inconvenience of Delivery Centers, involved a grid where the goal was to reduce the maximum distance from any 0 cell to the nearest delivery center by flipping at most one 0 to 1. Both problems demanded a deep understanding of data structures and algorithms, as well as careful planning for optimal solutions.
Interview Questions (2)
You are given an array product[] of size n, where each element is 0 or 1.
1 = variant B (needs to be converted)
0 = variant A (already correct)
Amazon wants to convert all products into variant A (0).
You are allowed to choose a subarray of length = k, and set exactly one element in that subarray to 0.
The cost of an operation = sum of values in that subarray before conversion.
Return the minimum cost to make the entire array all 0.
A city is represented as a grid:
Delivery centers are marked as 1
All other places are marked as 0
The distance between two cells is defined as d((x1,y1), (x2,y2)) = max(|x1-x2|, |y1-y2|).
The inconvenience of the grid is the maximum distance of any 0 from its nearest delivery center.
Amazon is planning to open one new delivery center. You may flip at most one 0 to 1.
Find the minimum inconvenience possible after this operation.
Preparation Tips
Prepared by focusing on algorithmic problem-solving techniques, particularly for dynamic programming and greedy algorithms. Worked on similar problems to understand the optimal approaches for handling large input sizes. Also, practiced multi-source BFS for grid-based problems to tackle the second question effectively.