Crushing The Technical Interview: Data Structures and Algorithms. The study guide for data structures and algorithms interviews (Python Edition)

1. Introduction
What to Expect
Why I Wrote This Book
Who This Book Is For
Conventions in this Book
2. The Interview Process
Overview
Recruiter Phone Interview
Coding Challenge
Coding Project
On-Site Interviews
Data Structures & Algorithms Interviews
System Design Interviews
The Process and Communication Interview
Manager/Team Matching Interviews
Now What Happens
3. Big-O Notation
Simplifying Big-O Notation
Constant Time
Logarithmic Time
Linear Time
Super-Linear Time
Polynomial Time
Exponential Time
Factorial Time: Final Boss Fight!
4. Software Theory
Introduction
Single Responsibility Principle (SRP)
Open-Closed Principle (OCP)
Liskov Substitution Principle (LSP)
Interface Segregation Principle (ISP)
Dependency Inversion Principle (DIP)
Don’t Repeat Yourself (DRY)
KISS Principle
OOP Design Patterns
5. Data Structures
What Is A Data Structure?
Arrays
Lists
Stacks
Queues
Linked Lists
Graphs
Trees
Heaps
Hash Maps
6. Algorithms
Bubble Sort
Merge Sort
Quick Sort
Insertion Sort
Tree Traversals
Breadth First Search (BFS)
Depth First Search (DFS)
A* Algorithm
Dijkstra’s Algorithm
Two Pointers
Sliding Window
Backtracking (N-Queens Problem)
Trie Data Structure
Topological Sort
Bucket Sort
Quickselect
Prefix Sum
Monotonic Stack
Union Find
Prim’s Algorithm (Minimum Spanning Trees)
Kruskal’s Algorithm
Binary Manipulation
Floyd’s Algorithm
Median-of-Medians Algorithm
Recursion with Memoization
Huffman Coding Algorithm
Red-Black Tree Algorithm
Ford-Fulkerson Algorithm (Edmonds-Karp)
Array Mutation
7. Practice Coding Problems
1. Arrays & Hashing: Character Pattern Matching
2. Arrays & Hashing: Product Price Pairing
3. Arrays & Hashing: Vocabulary Pattern Clusters
4. Heap/Priority Queue: Trending Hashtag Analysis
5. Arrays & Hashing: Supply Network Resilience Calculator
6. Sliding Window: Optimal Document Segment
7. Sliding Window: Extrema Product
8. Arrays & Hashing: Longest Palindromic Substring
9. Arrays & Hashing: Two Sum
10. Trees: Level Order Traversal
11. Dynamic Programming: Fibonacci with Memoization
12. Graphs: Number of Islands
13. Arrays & Hashing: First Non-Repeating Character
14. Linked List: Reverse a Linked List
15. Heap/Priority Queue: Balanced Network Traffic
16. Graphs: Dependency Resolver
17. Intelligent Cache System
18. Trees: Text Editor Line Tracker
19. Sliding Window: Message Rate Limiter
21: Arrays & Hashing: Circular Array Rotation Sequence
22. Greedy Algorithm: Optimized Task Scheduler
23. Greedy Algorithm: Interval Coverage Optimization
24. Graphs: Dynamic Maze Flood Fill
25. Heap/Priority Queue: Adaptive Resource Scheduler
26. Graphs: Distributed Cache Consistency
27. Arrays & Hashing: Maximum Subarray With Target Sum
28. Sliding Window: K-Nearest Neighbors
29. Backtracking: Matrix Circuit
30. Dynamic Programming: Artwork Gallery Heist
31. Sliding Window: Range Duplicate Finder
32. Stack: Temperature Forecast Analysis
33. Two Pointers: Scenic Skyline Viewpoints
34. Two Pointers: Mountain Valley Rainwater Collection
35. Greedy Algorithms: Maximum Property Value Appreciation
36. Arrays & Hashing: Frequency Threshold Detection
37. Arrays & Hashing: X-Sudoku Validator
38. Greedy Algorithms: Vehicle Convoy Formation
39. Stack: Maximum Productivity Zone
40. Matrix Operations: Layered Security Clearance Search
41. Binary Search: Document Processing Throughput
42. Binary Search: Encrypted Circular Buffer Search
43. Matrix Operations: Parallel Matrix Diagonal Sum
44. Binary Search: Version-Based Configuration Store
45. Binary Search: Minimum Processing Power
46. Trees: Clone Bi1nary Tree with Connection Pointers
47. Linked List: Rotate Linked List Around Pivot
48. Linked List: Interleave K Linked Lists
49. Trees: Path Matching Binary Tree
50. Trees: Symmetric Tree Transformation
51. Stack: Expression Tree Execution
52. Stack: Balanced Bracket Sequence Generator
53. Trees: Balanced Tree Reconstruction
54. Trees: Optimal Node Removal for Minimum Height
55. Tries: Context-Sensitive Search Suggestion System
56. Tries: Fuzzy Word Finder
57. Binary Search: Minimum Allocation Threshold for Equal Array Groups
58. Binary Search: Kth Ancestral Element in Sorted Arrays
59. Graphs: Key Collection Sequence
60. Arrays & Hashing: Group Anagrams By Frequency
61. Dynamic Programming: Maximum Product Path
62. Graphs: Island Count with Restrictions
63. Binary Search: Find Kth Element in Two Sorted Arrays
64. Stack: Evaluate Reverse Polish Notation with Custom Operations
65. Matrix Operations: Optimal Kennel Assignment
66. Matrix Operations: Wedding Seating Arrangement
67. Linked List: Boat Fleet Chain Inspection
68. Linked List: Baseball Lineup Rotation
69. Two Pointers: Coffee Bean Blend Matcher
70. Sliding Window: Holiday Card Joy Maximizer
71. Stack: Fashion Display Stack Optimizer
72. Heap/Priority Queue: Restaurant Priority Seating System
73. Backtracking: Optimal Race Day Strategy
74. Graphs: Detective Case Assignment Network
75. Dynamic Programming: Seasonal Orange Grove Harvest
8. Problem Solutions
1. Character Pattern Matching
2. Product Price Pairing
3. Vocabulary Pattern Clusters
4. Trending Hashtag Analysis
5. Supply Network Resilience Calculator
6. Optimal Document Segment
7. Sliding Window Extrema Product
8. Longest Palindromic Substring
9. Two Sum
10. Level Order Traversal
11. Fibonacci with Memoization
12. Number of Islands
13. First Non-Repeating Character
14. Reverse a Linked List
15. Balanced Network Traffic
16. Dependency Resolver
17. Intelligent Cache System
18. Text Editor Line Tracker
19. Message Rate Limiter
20. Evidence Processing Queue
21: Circular Array Rotation Sequence
22. Optimized Task Scheduler
23. Interval Coverage Optimization
24. Dynamic Maze Flood Fill
25. Adaptive Resource Scheduler
26. Distributed Cache Consistency
27. Maximum Subarray With Target Sum
28. K-Nearest Neighbors in Sliding Window
29: Matrix Circuit
30. Artwork Gallery Heist
31. Range Duplicate Finder
32. Temperature Forecast Analysis
33. Scenic Skyline Viewpoints
34. Mountain Valley Rainwater Collection
35. Maximum Property Value Appreciation
36. Frequency Threshold Detection
37. X-Sudoku Validator
38. Vehicle Convoy Formation
39. Maximum Productivity Zone
40. Layered Security Clearance Search
41. Document Processing Throughput
42. Encrypted Circular Buffer Search
43. Parallel Matrix Diagonal Sum
44. Version-Based Configuration Store
45. Minimum Processing Power
46. Clone Binary Tree with Connection Pointers
47. Rotate Linked List Around Pivot
48. Interleave K Linked Lists
49. Path Matching Binary Tree
50. Symmetric Tree Transformation
51. Expression Tree Execution
52. Balanced Bracket Sequence Generator
53. Balanced Tree Reconstruction
54. Optimal Node Removal for Minimum Height
55. Context-Sensitive Search Suggestion System
56. Fuzzy Word Finder
57. Minimum Allocation Threshold for Equal Array Groups
58. Kth Ancestral Element in Sorted Arrays
59. Key Collection Sequence
60. Group Anagrams By Frequency
61. Maximum Product Path
62. Island Count with Restrictions
63. Find Kth Element in Two Sorted Arrays
64. Evaluate Reverse Polish Notation with Custom Operations
65. Optimal Kennel Assignment
66. Wedding Seating Arrangement
67. Boat Fleet Chain Inspection
68. Baseball Lineup Rotation
69. Coffee Bean Blend Matcher
70. Holiday Card Joy Maximizer
71. Fashion Display Stack Optimizer
72. Restaurant Priority Seating System
73. Optimal Race Day Strategy
74. Detective Case Assignment Network
75. Seasonal Orange Grove Harvest
9. Tips for Hiring Managers & Interviewers
Take-Home Coding Project Challenges
Why Top Tech Companies Don’t Use Take-Home Tests
A Better Hiring Funnel
For Candidates
Final Thoughts
10. Resources
Top Leetcode Problems
Recommended Books
11. Appendix: Take Home Code Project
In-Memory Cache For Online Advertising Agency
About the Author

Learn the process of interviewing for a software development role, how to prepare, and all the information you will need to make it through the data structures and algorithms interview.
This book covers what to expect in each stage of the interview process, how to describe the complexity of an algorithm using Big-O notation, the basic software theories you will need to succeed, and how to answer behavioral questions meaningfully. Then you will learn the most important data structures and the minimum number of targeted algorithms need in order to crush your coding interview. There are 75 unique coding problems for you to practice on along with the solutions. Once you are done, you should be able to map the patterns you learn onto any problem and solve them with ease.
This book is available in various editions based on the programming language of your choice. This is the Python Edition.