If you don't understand sth, that's okay. What you need to do is to read a lot of material(I mean a few hundred pages) and complete all the exercises on your own. But remember to start with material that fits your ability level. Yes, that's how we get things done. Very simple ! So easy !

So tell me, what are you eager to know ?

I am very interested in how to use programming to solve various real-world problems.

Great ! Then allow me to introduce you to the best introductory material: Introduction to Algorithms (Fourth Edition)

Excellent ! Let’s get to work !

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Before reading the solution to a problem in the book, I like to challenge myself to try to solve it myself. So exciting !!!

You must implement all the algorithms on your own, complete all the exercises on your own, and prove and derive all the theorems on your own. Turn off Copilot and only turn to ChatGPT for some advice when you are stuck for at least 5 minutes. This method may seem slow, but it is actually the most efficient way to learn. Wow, that's so exciting ! Let's do it !

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Learning Standards:

Phase 1: Choose any theorem or exercise from the textbook and be able to prove or solve it entirely on your own.

Phase 2: "What I cannot create, I do not understand." Rewrite the entire textbook from memory, without referring to the original text.

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2023/1/9 18:00 - 1/12: round 1

2024/5/6 12:00 - 6/13: round 2

2024/9/6 21:00 - now: continue round 2, start from ch14: dynamic programming

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2018: https://github.com/walkccc/CLRS

"clrsPython" is copied from the official website

https://github.com/OccupyMars2025/Solutions-to-Introduction-to-Algorithms-Third-Edition

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useful tools:

Data Structure Visualizations

https://app.diagrams.net/

use networkx, graphviz to draw graphs

https://networkx.org/documentation/stable/auto_examples/index.html

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TODO: all the exercises and problems in ch1-ch11 in the 4th edition book, I have only completed them in ch1-ch11 in the 3rd edition book

Goal: 2024/5/6 12:00 - 5/25 22:00: complete learning this book

• 2024/5/6 12:00 - 5/7 22:00 : Chapter 2 Getting Started
• 5/7 22:00 - 5/8 22:10: Chapter 3: Characterizing Running Times, page 71-98
• 5/8 22:10 - 5/12 19:30 : Chapter 4: Divide-and-Conquer, page 98-148

TODO: Section 4.6, 4.7 and Chapter 4 Problems

• 5/12 19:30 - 5/17 8:30: Chapter 5: Probabilistic Analysis and Randomized Algorithms

TODO: page 151, chapter 5 Exercises

TODO: page 166-178

• 5/17 8:30 - 5/18 15:40 : Chapter 6: Heapsort, page 178-204

TODO: all exercises and problems in Chapter 6

• 5/18 15:40 - 5/20 19:00: Chapter 7: Quicksort, page 204-227

TODO: page 220-226

• 5/20 19:00 - 5/23 8:30 : Chapter 8: Sorting in Linear Time, page 227-249

TODO: chapter 8: Problems

• 5/23 8:30 - 5/25 10:30: Chapter 9: Medians and Order Statistics, page 249-270
• 5/25 10:30 - 5/26 6:30: Chapter 10: Elementary Data Structures , page 270-294

TODO: chapter 9

TODO: Exercise 10.2-8

TODO: chapter 11.2 - 11.5

TODO: page 289-293

• 5/26 6:30 - 5/28 12:10: Chapter 11: Hash Tables, page 294-334
• 5/28 12:10 - 6/6 20:00: Chapter 12: Binary Search Trees, page 334-353

TODO: From Chapter 12 on, do exercises and problems using AI. You need to redo all the exercises and problems in Chapter 1-11 by the help of AI

• 6/6 20:00 - 6/13 20:00 : Chapter 13: Red-Black Trees, page 353-382

TODO: Exercise 13.4-9, Problems in chapter 13

• 6/13 20:00 - 6/16, 8/7 20:45- : Chapter 14: Dynamic Programming, page 362-417
• 9/6 21:20 - : Chapter 14: Dynamic Programming, page 362-417

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Introduction to Algorithms, Fourth Edition

Time is Money, Efficiency is Life

Algorithms as a Technology

"We hope that this textbook provides you with an enjoyable introduction to the field of algorithms. We have attempted to make every algorithm accessible and interesting. Enjoy it !"

"CLRS" (Cormen, Leiserson, Rivest, Stein)

official website of this book

reference:

https://github.com/walkccc/CLRS
https://walkccc.me/CLRS/
https://sites.math.rutgers.edu/~ajl213/CLRS/CLRS.html
https://github.com/walkccc/CLRS-cpp

tools:

install all the latest LLVM toolchain: https://apt.llvm.org/