Amazon OA Real Questions Analysis: Common Algorithm Pitfalls for International Students and How to Avoid Them

Introduction
When preparing for Amazon's Online Assessment (OA), international students often encounter challenges in algorithmic problem-solving. Below are common pitfalls and strategies to help you navigate these challenges effectively.
Common Algorithm Pitfalls
Inefficient Time Complexity
Many students overlook time complexity, leading to solutions that perform poorly on large datasets.
Poor Boundary Handling
Code often fails to address edge cases like empty inputs or single-element arrays.
Inappropriate Data Structure Selection
Using arrays instead of linked lists for frequent insertions/deletions, or vice versa, reduces efficiency.
Recursion Depth Issues
Recursive solutions may cause stack overflows, especially with large datasets.
Dynamic Programming Errors
Incorrect state definitions or transition equations render DP solutions ineffective.
Cycle Detection in Graph Algorithms
Ignoring cycles in graph problems can lead to infinite loops.
Avoidance Strategies
Optimize Time Complexity
Prefer algorithms with lower time complexity (e.g., binary search over linear search, hash tables over nested loops).
Account for All Boundary Conditions
List edge cases before coding and ensure they are handled correctly.
Choose Appropriate Data Structures
Use linked lists for dynamic operations and hash tables for fast lookups.
Control Recursion Depth
Use tail recursion or iterative approaches to avoid stack overflows.
Define DP States Correctly
Carefully design state definitions and transition equations to ensure correctness.
Detect Cycles in Graphs
Use visit markers or union-find to handle cycles and prevent infinite loops.
Real Question Analysis
Question 1: Diameter of Binary Tree
Problem: Given a binary tree, find the length of its diameter (the longest path between any two nodes, which may or may not pass through the root).

Approach:

Use recursion to traverse the tree.
For each node, compute the depths of its left and right subtrees and update the maximum diameter.
Return the current node's depth (max of left/right depths + 1).

Solution Code:

python
运行
class Solution:

def diameterOfBinaryTree(self, root: TreeNode) -> int:

self.diameter = 0

    def depth(node):  
        if not node:  
            return 0  
        left_depth = depth(node.left)  
        right_depth = depth(node.right)  
        self.diameter = max(self.diameter, left_depth + right_depth)  
        return max(left_depth, right_depth) + 1  

    depth(root)  
    return self.diameter  

Question 2: Longest Palindromic Substring
Problem: Given a string s, find the longest palindromic substring. Assume the maximum length of s is 1000.

Approach:

Use dynamic programming with a 2D array dp, where dp[i][j] indicates if s[i:j] is a palindrome.
Initialize single characters as palindromes.
Traverse the string to update dp and track the longest palindrome's indices.

Solution Code:

python
运行
class Solution:

def longestPalindrome(self, s: str) -> str:

n = len(s)

dp = [[False] * n for _ in range(n)]

start, max_length = 0, 1

    for i in range(n):  
        dp[i][i] = True  

    for j in range(1, n):  
        for i in range(j):  
            if s[i] == s[j] and (j - i < 3 or dp[i+1][j-1]):  
                dp[i][j] = True  
                if j - i + 1 > max_length:  
                    start = i  
                    max_length = j - i + 1  

    return s[start:start + max_length]  

By understanding these common pitfalls and practicing with real questions, international students can better prepare for Amazon OA, avoid algorithmic mistakes, and improve their interview success rate.