Amazon Software Development Engineer II Interview Questions, Process, and Tips

Dsa, array, dp, backtracking

Q1. 2 sum array queston
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Q2. Container problem
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The container problem involves efficiently packing items into containers to minimize wasted space.
• Use algorithms like First Fit, Best Fit, or Next Fit to optimize packing efficiency.

• Consider the size and shape of items being packed to determine the best container arrangement.

• Utilize dynamic programming or greedy algorithms to solve the container packing problem efficiently.
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Round 1 was a technical/coding round. There were 2 simple linked-list and LRU cache questions.

Round 2 was also a tech/coding round. The 1st question was about from tree and second was from string (which could be done using map and array).

Q1. What was your role in your previous organization? (In details)
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Q2. What projects have you worked on? (In details)
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Standard questions, Don't Remember

Q1. 2 LPS, Combinations Question
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Q2. 2 LPS, LLD
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Q1. 2 LPS, 1 Coding
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Tough and was mostly out of leet code type

Q1. About code and DSA
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Q2. System Design and architecture
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Q1. Coin change problem
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The coin change problem involves finding the minimum number of coins needed to make a certain amount of change.
• Start by creating an array to store the minimum number of coins needed for each amount from 0 to the target amount.

• Iterate through each coin denomination and update the minimum number of coins needed for each amount.

• Return the minimum number of coins needed for the target amount.
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Q2. Min heap related questions
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Q1. Tree traversal problem
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Tree traversal problem involves visiting each node in a tree data structure in a specific order.
• There are three main types of tree traversal: in-order, pre-order, and post-order.

• In-order traversal visits the left subtree, then the root, then the right subtree.

• Pre-order traversal visits the root, then the left subtree, then the right subtree.

• Post-order traversal visits the left subtree, then the right subtree, then the
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Q2. Longest common subsequence
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Longest common subsequence is the longest sequence of characters that appear in the same order in two or more strings.
• Use dynamic programming to solve this problem efficiently.

• Create a 2D array to store the lengths of longest common subsequences of substrings.

• Traverse the array to find the longest common subsequence.
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Q1. Whatsapp LLD and HLD
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Q1. Two coding questions for 90 minutes
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Q2. Bunch of questions to be answered (select out of two options) to describe you, your work style, how you handle situation
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