Absolute Beginner’s Guide to Algorithms

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Absolute Beginner’s Guide to Algorithms

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Part I: Data Structures

 

Chapter 1. Introduction to Data Structures ………………………………………………………… 1

     Right Tool for the Right Job ………………………………………………………………………… 2

     Back to Data Structures ………………………………………………………………………………. 5

     Conclusion ………………………………………………………………………………………………….. 6

 

Chapter 2. Big-O Notation and Complexity Analysis …………………………………………… 7

     It’s Example Time ………………………………………………………………………………………… 8

     It’s Big-O Notation Time! ……………………………………………………………………………11

     Conclusion …………………………………………………………………………………………………15

 

Chapter 3. Arrays …………………………………………………………………………………………. 17

     What Is an Array? ……………………………………………………………………………………….18

     Array Implementation / Use Cases ……………………………………………………………..24

     Arrays and Memory ……………………………………………………………………………………26

     Performance Considerations ………………………………………………………………………30

     Conclusion …………………………………………………………………………………………………32

 

Chapter 4. Linked Lists ………………………………………………………………………………….. 35

     Meet the Linked List …………………………………………………………………………………..36

     Linked List: Time and Space Complexity …………………………………………………….40

     Linked List Variations ………………………………………………………………………………….41

     Implementation ………………………………………………………………………………………….44

     Conclusion …………………………………………………………………………………………………52

 

Chapter 5. Stacks ………………………………………………………………………………………….. 53

     Meet the Stack …………………………………………………………………………………………..54

     A JavaScript Implementation ……………………………………………………………………..56

     Stacks: Time and Space Complexity …………………………………………………………..58

     Conclusion …………………………………………………………………………………………………59

 

Chapter 6. Queues ……………………………………………………………………………………….. 61

     Meet the Queue ………………………………………………………………………………………..62

     A JavaScript Implementation ……………………………………………………………………..64

     Queues: Time and Space Complexity …………………………………………………………66

     Conclusion …………………………………………………………………………………………………67

 

Chapter 7. Trees …………………………………………………………………………………………… 69

     Trees 101 …………………………………………………………………………………………………..70

     Height and Depth ………………………………………………………………………………………75

     Conclusion …………………………………………………………………………………………………77

 

Chapter 8. Binary Trees …………………………………………………………………………………. 79

     Meet the Binary Tree ………………………………………………………………………………….80

     A Simple Binary Tree Implementation …………………………………………………………86

     Conclusion …………………………………………………………………………………………………89

 

Chapter 9. Binary Search Trees ……………………………………………………………………….. 91

     It’s Just a Data Structure …………………………………………………………………………….93

     Implementing a Binary Search Tree …………………………………………………………..103

     Performance and Memory Characteristics …………………………………………………110

     Conclusion ……………………………………………………………………………………………….112

 

Chapter 10. Heaps ………………………………………………………………………………………… 113

     Meet the Heap …………………………………………………………………………………………114

     Heap Implementation ………………………………………………………………………………126

     Performance Characteristics ……………………………………………………………………..132

     Conclusion ……………………………………………………………………………………………….134

 

Chapter 11. Hashtable (aka Hashmap or Dictionary) ………………………………………….. 137

     A Very Efficient Robot ………………………………………………………………………………138

     From Robots to Hashing Functions …………………………………………………………..142

     From Hashing Functions to Hashtables …………………………………………………….145

     JavaScript Implementation/Usage …………………………………………………………….148

     Dealing with Collisions ……………………………………………………………………………..150

     Performance and Memory ………………………………………………………………………..151

     Conclusion ……………………………………………………………………………………………….153

 

Chapter 12. Trie (aka Prefix Tree) ……………………………………………………………………. 155

     What Is a Trie? …………………………………………………………………………………………156

     Diving Deeper into Tries …………………………………………………………………………..167

     Many More Examples Abound! ………………………………………………………………..172

     Implementation Time ……………………………………………………………………………….173

     Performance …………………………………………………………………………………………….179

     Conclusion ……………………………………………………………………………………………….181

 

Chapter 13. Graphs ………………………………………………………………………………………. 183

     What Is a Graph? ……………………………………………………………………………………..184

     Graph Implementation ……………………………………………………………………………..190

     Conclusion ……………………………………………………………………………………………….196

 

Part II: Algorithms

 

Chapter 14. Introduction to Recursion …………………………………………………………….. 199

     Our Giant Cookie Problem ……………………………………………………………………….200

     Recursion in Programming ……………………………………………………………………….202

     Conclusion ……………………………………………………………………………………………….206

 

Chapter 15. Fibonacci and Going Beyond Recursion …………………………………………. 207

     Recursively Solving the Fibonacci Sequence …………………………………………….209

     Recursion with Memoization …………………………………………………………………….213

     Taking an Iteration-Based Approach …………………………………………………………215

     Going Deeper on the Speed ……………………………………………………………………217

     Conclusion ……………………………………………………………………………………………….218

 

Chapter 16. Towers of Hanoi ………………………………………………………………………….. 221

     How Towers of Hanoi Is Played ………………………………………………………………..222

     The Single Disk Case ……………………………………………………………………………….223

     It’s Two Disk Time …………………………………………………………………………………….224

     Three Disks ………………………………………………………………………………………………225

     The Algorithm ………………………………………………………………………………………….228

     The Code Solution …………………………………………………………………………………..229

     Check Out the Recursiveness! ………………………………………………………………….231

     It’s Math Time …………………………………………………………………………………………..232

     Conclusion ……………………………………………………………………………………………….234

 

Chapter 17. Search Algorithms and Linear Search …………………………………………….. 235

     Linear Search ……………………………………………………………………………………………236

     Conclusion ……………………………………………………………………………………………….241

 

Chapter 18. Faster Searching with Binary Search ………………………………………………. 243

     Binary Search in Action …………………………………………………………………………….243

     The JavaScript Implementation ………………………………………………………………..250

     Runtime Performance ……………………………………………………………………………….254

     Conclusion ……………………………………………………………………………………………….257

 

Chapter 19. Binary Tree Traversal ……………………………………………………………………. 259

     Breadth-First Traversal ………………………………………………………………………………260

     Depth-First Traversal ………………………………………………………………………………..265

     Implementing Our Traversal Approaches ………………………………………………….270

     Performance of Our Traversal Approaches ………………………………………………..278

     Conclusion ……………………………………………………………………………………………….279

 

Chapter 20. Depth-First Search (DFS) and Breadth-First Search (BFS) ………………….. 281

     A Tale of Two Exploration Approaches ……………………………………………………..282

     It’s Example Time ……………………………………………………………………………………..285

     When to Use DFS? When to Use BFS? ……………………………………………………..298

     A JavaScript Implementation ……………………………………………………………………300

     Performance Details …………………………………………………………………………………307

     Conclusion ……………………………………………………………………………………………….308

 

Chapter 21. Quicksort …………………………………………………………………………………… 309

     A Look at How Quicksort Works ……………………………………………………………….310

     Another Simple Look ……………………………………………………………………………….314

     It’s Implementation Time ………………………………………………………………………….319

     Performance Characteristics ……………………………………………………………………..322

     Conclusion ……………………………………………………………………………………………….323

 

Chapter 22. Bubblesort …………………………………………………………………………………. 325

     How Bubblesort Works …………………………………………………………………………….326

     Walkthrough …………………………………………………………………………………………….329

     The Code …………………………………………………………………………………………………333

     Conclusion ……………………………………………………………………………………………….333

 

Chapter 23. Insertion Sort ……………………………………………………………………………… 335

     How Insertion Sort Works …………………………………………………………………………336

     One More Example ………………………………………………………………………………….347

     Algorithm Overview and Implementation …………………………………………………349

     Performance Analysis ……………………………………………………………………………….351

     Conclusion ……………………………………………………………………………………………….353

 

Chapter 24. Selection Sort …………………………………………………………………………….. 355

     Selection Sort Walkthrough ………………………………………………………………………356

     Algorithm Deep Dive ……………………………………………………………………………….364

     The JavaScript Implementation ………………………………………………………………..366

     Conclusion ……………………………………………………………………………………………….369

 

Chapter 25. Mergesort ………………………………………………………………………………….. 371

     How Mergesort Works ……………………………………………………………………………..372

     Mergesort: The Algorithm Details …………………………………………………………….379

     Looking at the Code ………………………………………………………………………………..380

     Conclusion ……………………………………………………………………………………………….381

 

Conclusion …………………………………………………………………………………………………..383

 

Index ……………………………………………………………………………………………………………. 387

Kirupa Chinnathambi has spent most of his life teaching others to love web development as much as he does. He founded KIRUPA, one of the Web’s most popular free web development education resources, serving 210,000+ registered members. Now a product manager at Google, he has authored several books, including Learning React (2017). He holds a B.S. in computer science from MIT.

A hands-on, easy-to-comprehend guide that is perfect for anyone who needs to understand algorithms.

With the explosive growth in the amount of data and the diversity of computing applications, efficient algorithms are needed now more than ever. Programming languages come and go, but the core of programming–algorithms and data structures–remains the same. 

Absolute Beginner’s Guide to Algorithms is the fastest way to learn algorithms and data structures. Using helpful diagrams and fully annotated code samples in Javascript, you will start with the basics and gradually go deeper and broader into all the techniques you need to organize your data.  

  • Start fast with data structures basics: arrays, stacks, queues, trees, heaps, and more
  • Walk through popular search, sort, and graph algorithms
  • Understand Big-O notation and why some algorithms are fast and why others are slow
  • Balance theory with practice by playing with the fully functional JavaScript implementations of all covered data structures and algorithms

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professional, higher education, Employability, IT Professional, Y-AN SOFTWARE ENGINEERING