A Common-Sense Guide to Data Structures and Algorithms

Resources

• A Common-Sense Guide to Data Structures and Algorithms, Second Edition: Level Up Your Core Programming Skills by Jay Wengrow

Chapter Checklist

• 1. Why Data Structures Matter
  • The Array: The Foundational Data Structure
  • Reading
  • Searching
  • Insertion
  • Deletion
  • Sets: How a Single Rule Can Affect Efficiency
  • Wrapping Up
• 2. Why Algorithms Matter
  • Ordered Arrays
  • Searching an Ordered Array
  • Binary Search
  • Binary Search vs. Linear Search
  • Wrapping Up
• 3. Oh Yes! Big O Notation
  • Big O: Count the Steps
  • Constant Time vs. Linear Time
  • Same Algorithm, Different Scenarios
  • An Algorithm of the Third Kind
  • Logarithms
  • O(log N) Explained
  • Practical Examples
  • Wrapping Up
• 4. Speeding Up Your Code with Big O
  • Bubble Sort
  • Bubble Sort in Action
  • Bubble Sort Implemented
  • The Efficiency of Bubble Sort
  • A Quadratic Problem
  • A Linear Solution
  • Wrapping Up
• 5. Optimizing Code with and Without Big O
  • Selection Sort
  • Selection Sort in Action
  • Selection Sort Implemented
  • The Efficiency of Selection Sort
  • Ignoring Constants
  • The Role of Big O
  • A Practical Example
  • Wrapping Up
• 6. Optimizing for Optimistic Scenarios
  • Insertion Sort
  • Insertion Sort in Action
  • Insertion Sort Implemented
  • The Efficiency of Insertion Sort
  • The Average Case
  • A Practical Example
  • Wrapping Up
• 7. Blazing Fast Lookup with Hash Tables
  • Enter the Hash Table
  • Hashing with Hash Functions
  • Building a Thesaurus for Fun and Profit, but Mainly Profit
  • Dealing with Collisions
  • The Great Balancing Act
  • Practical Examples
  • Wrapping Up
• 8. Crafting Elegant Code with Stacks and Queues
  • Stacks
  • Stacks in Action
  • Queues
  • Queues in Action
  • Wrapping Up
• 9. Recursively Recurse with Recursion
  • Recurse Instead of Loop
  • The Base Case
  • Reading Recursive Code
  • Recursion in the Eyes of the Computer
  • Recursion in Action
  • Wrapping Up
• 10. Recursive Algorithms for Speed
  • Partitioning
  • Quicksort
  • The Efficiency of Quicksort
  • Worst-Case Scenario
  • Quickselect
  • Wrapping Up
• 11. Node-Based Data Structures
  • Linked Lists
  • Implementing a Linked List
  • Reading
  • Searching
  • Insertion
  • Deletion
  • Linked Lists in Action
  • Doubly Linked Lists
  • Wrapping Up
• 12. Speeding Up All the Things with Binary Trees
  • Binary Trees
  • Searching
  • Insertion
  • Deletion
  • Binary Trees in Action
  • Wrapping Up
• 13. Connecting Everything with Graphs
  • Graphs
  • Breadth-First Search
  • Graph Databases
  • Weighted Graphs
  • Dijkstra’s Algorithm
  • Wrapping Up
• 14. Dealing with Space Constraints
  • Big O Notation as Applied to Space Complexity
  • Trade-Offs Between Time and Space
  • Parting Thoughts