Stage II: Easy Questions

Linked List

Pattern: Conceptual Understanding

1. The Core Trade-Off

Problem: Based on the "Mission Briefing," what is the primary advantage of a Linked List over an Array for dynamic data, and what is its main disadvantage regarding data access?

Concept Tested: Understanding the fundamental time complexity trade-offs between Arrays and Linked Lists (O(1) insertion/deletion vs. O(n) access).

Analysis:

Advantage: The primary advantage of a Linked List is its efficient insertion and deletion. Unlike an array, which requires shifting all subsequent elements (an O(n) operation), a linked list only needs to redirect a few pointers, which is a constant time O(1) operation.

Disadvantage: The main disadvantage is slow access time. To get to the n-th element in a linked list, you must traverse through all n-1 preceding nodes, making it an O(n) operation. An array allows for instant O(1) access via an index.

2. Linked List Varieties

Problem: Using the "train car" analogy, explain the structural difference between a Singly, Doubly, and Circular Linked List. For what type of application is a Doubly Linked List particularly useful?

Concept Tested: Differentiating between the types of linked lists and their specific use cases.

Analysis:

Singly Linked List: A standard train where each car points only to the car in front of it (next pointer).

Doubly Linked List: An advanced train where each car has couplers on both ends, pointing to the car in front (next) and the car behind (prev). It is particularly useful for implementing a browser's back/forward history or an undo/redo feature.

Circular Linked List: A circular train track where the last car connects back to the first car, forming a continuous loop.

Pattern: Foundational Pointer Manipulation

These are classic problems that test your ability to traverse a list and manipulate next pointers.

3. Reverse Linked List

Problem: Given the head of a singly linked list, reverse the list, and return the new head.

Concept Tested: Iterative pointer manipulation, keeping track of previous, current, and next nodes.

Companies: Amazon, Microsoft, Apple, Facebook (Meta), Google

4. Merge Two Sorted Lists

Problem: You are given the heads of two sorted linked lists. Merge the two lists into one sorted list.

Concept Tested: Simultaneously traversing two lists and comparing their nodes to build a new, sorted list.

Companies: Amazon, Microsoft, Google, Apple, LinkedIn

5. Remove Nth Node From End of List

Problem: Given the head of a linked list, remove the n-th node from the end of the list and return its head.

Concept Tested: The classic "two-pointer gap" technique.

Companies: Amazon, Facebook (Meta), Microsoft, Bloomberg

6. Palindrome Linked List

Problem: Given the head of a singly linked list, return true if it is a palindrome.

Concept Tested: Combining multiple patterns: finding the middle, reversing the second half, and comparing.

Companies: Amazon, Facebook (Meta), Apple, Google

Stacks

Pattern: Conceptual Understanding

These questions test your direct comprehension of the LIFO principle and its direct applications.

1. The LIFO Principle & Use Cases

Problem: Explain the "Last-In, First-Out" (LIFO) principle using the "stack of plates" analogy. Provide two real-world examples mentioned in the text where this behavior is essential.

Concept Tested: Understanding the core LIFO principle and its direct applications.

2. Implementation Trade-offs

Problem: What are the two common ways to implement a Stack data structure as described in the blueprint? Why might a Linked List implementation be considered more theoretically efficient in all cases compared to a dynamic array?

Concept Tested: Differentiating between array-based and linked-list-based stack implementations.

Pattern: Classic Stack Applications

These are the quintessential problems that perfectly demonstrate the power of the LIFO principle for validation and tracking.

3. Valid Parentheses

Problem: Given a string containing just '(', ')', '{', '}', '[' and ']', determine if the input string is valid.

Concept Tested: Using a stack to match opening and closing pairs.

Companies: Amazon, Google, Facebook (Meta), Microsoft, Bloomberg

4. Min Stack

Problem: Design a stack that supports push, pop, top, and retrieving the minimum element in constant time.

Concept Tested: Augmenting a standard stack with a second stack to track minimums.

Companies: Amazon, Bloomberg, Apple, Microsoft, Google

5. Implement Queue using Stacks

Problem: Implement a First-In-First-Out (FIFO) queue using only two stacks.

Concept Tested: Deep understanding of stack (LIFO) and queue (FIFO) properties.

Companies: Amazon, Microsoft, Bloomberg, Oracle

Queue

Pattern: Foundational Queue Applications

These problems represent the most common applications of the Queue data structure.

3. Binary Tree Level Order Traversal

Problem: Given the root of a binary tree, return the level order traversal of its nodes' values.

Concept Tested: This is the quintessential application of Breadth-First Search (BFS), for which a queue is the essential tool.

Companies: Amazon, Facebook (Meta), Microsoft, Apple, LinkedIn

4. Number of Recent Calls

Problem: Count the number of recent requests within a certain time frame.

Concept Tested: Using a queue to maintain a "sliding window" of data.

Companies: Google, Amazon, Microsoft

Hashing

Pattern: Foundational Hash Map Applications

These problems demonstrate the power of a hash map for lookups, frequency counting, and grouping.

3. Two Sum

Problem: Given an array of integers and a target, return indices of two numbers that add up to target.

Concept Tested: The classic hash map pattern of storing seen values for instant lookups.

Companies: Amazon, Google, Facebook (Meta), Apple, Microsoft

4. Valid Anagram

Problem: Given two strings s and t, return true if t is an anagram of s.

Concept Tested: Using a hash map as a frequency counter.

Companies: Amazon, Microsoft, Apple, Bloomberg

5. Group Anagrams

Problem: Given an array of strings, group the anagrams together.

Concept Tested: Using a computed key (the sorted string) to group items in a hash map.

Companies: Amazon, Facebook (Meta), Google, Bloomberg, Microsoft