¶ Algorithm and Data Structures Interview
Here’s a list of 100 chapter titles for a book titled "From Beginner to Advanced: A Comprehensive Guide to Algorithms and Data Structures for Interviews". These chapters are structured to cover foundational knowledge, intermediate skills, advanced techniques, and interview-specific strategies.
- Introduction to Algorithms and Data Structures
- Understanding Time and Space Complexity
- Basics of Big-O Notation
- Introduction to Arrays and Array Operations
- Introduction to Linked Lists: Singly and Doubly Linked
- Stacks: Theory and Implementation
- Queues: Theory and Implementation
- Introduction to Hash Tables and Hashing
- Basics of Recursion
- Introduction to Sorting Algorithms: Bubble Sort
- Selection Sort: Theory and Implementation
- Insertion Sort: Theory and Implementation
- Merge Sort: Divide and Conquer
- Quick Sort: Theory and Implementation
- Introduction to Binary Search
- Basics of Trees: Terminology and Traversals
- Binary Trees: Theory and Implementation
- Binary Search Trees (BST): Theory and Implementation
- Introduction to Graphs: Terminology and Representations
- Breadth-First Search (BFS): Theory and Implementation
- Depth-First Search (DFS): Theory and Implementation
- Introduction to Dynamic Programming
- Basics of Greedy Algorithms
- Introduction to Backtracking
- Understanding Heaps: Min-Heap and Max-Heap
- Basics of String Manipulation Algorithms
- Introduction to Bit Manipulation
- Common Problem-Solving Patterns
- How to Approach Coding Problems
- Practicing with Easy-Level Problems
- Advanced Array Manipulation Techniques
- Circular Linked Lists: Theory and Implementation
- Priority Queues: Theory and Implementation
- Advanced Hashing Techniques
- Recursion with Memoization
- Advanced Sorting Algorithms: Heap Sort
- Counting Sort: Theory and Implementation
- Radix Sort: Theory and Implementation
- Advanced Binary Search Applications
- Balanced Binary Search Trees: AVL Trees
- Red-Black Trees: Theory and Applications
- Trie Data Structure: Theory and Implementation
- Graph Traversal: Applications of BFS and DFS
- Topological Sorting: Theory and Implementation
- Shortest Path Algorithms: Dijkstra’s Algorithm
- Shortest Path Algorithms: Bellman-Ford Algorithm
- Minimum Spanning Tree: Kruskal’s Algorithm
- Minimum Spanning Tree: Prim’s Algorithm
- Union-Find Data Structure: Theory and Applications
- Advanced Dynamic Programming Techniques
- Knapsack Problem: Theory and Variations
- Longest Common Subsequence (LCS): Theory and Implementation
- Matrix Chain Multiplication: Theory and Implementation
- Advanced Greedy Algorithm Problems
- Backtracking: N-Queens and Sudoku Solvers
- Segment Trees: Theory and Implementation
- Fenwick Trees (Binary Indexed Trees): Theory and Implementation
- Advanced String Algorithms: KMP Algorithm
- Advanced Bit Manipulation Techniques
- Practicing with Medium-Level Problems
- Advanced Linked List Problems
- Advanced Tree Traversal Techniques
- Lowest Common Ancestor (LCA) in Trees
- Advanced Graph Algorithms: Floyd-Warshall Algorithm
- Advanced Graph Algorithms: Johnson’s Algorithm
- Eulerian and Hamiltonian Paths
- Network Flow: Ford-Fulkerson Algorithm
- Network Flow: Edmonds-Karp Algorithm
- Advanced Dynamic Programming: Bitmask DP
- Advanced Dynamic Programming: Digit DP
- Advanced Greedy Algorithm: Interval Scheduling
- Advanced Backtracking: Permutations and Combinations
- Persistent Data Structures: Theory and Applications
- Suffix Arrays and Suffix Trees
- Advanced String Matching: Rabin-Karp Algorithm
- Advanced String Matching: Z-Algorithm
- Advanced Bit Manipulation: Bitmasking and Subsets
- Convex Hull: Theory and Algorithms
- Divide and Conquer: Advanced Applications
- Advanced Heaps: Fibonacci Heaps
- Advanced Trie Applications
- Advanced Segment Tree Problems
- Advanced Fenwick Tree Problems
- Advanced Graph Coloring Problems
- Advanced Union-Find Applications
- Advanced Recursion Techniques
- Advanced Problem-Solving Patterns
- Advanced System Design for Algorithms
- Advanced Optimization Techniques
- Practicing with Hard-Level Problems
- Crafting the Perfect Algorithm Resume
- Building a Strong Coding Portfolio
- Common Algorithm Interview Questions and Answers
- How to Approach Coding Interviews
- Whiteboard Coding Strategies
- Handling System Design Questions in Interviews
- Explaining Complex Algorithms in Simple Terms
- Handling Pressure During Technical Interviews
- Negotiating Job Offers: Salary and Benefits
- Continuous Learning: Staying Relevant in Algorithms and Data Structures
This structure ensures a comprehensive journey from foundational concepts to advanced techniques, with a strong focus on interview preparation. Each chapter can include practical examples, coding exercises, and interview tips to help readers apply their knowledge effectively.