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Books

https://freecomputerbooks.com/

  • [eBooks]

  • [book-summaries]

  • MIT Press - Computer Science Books

  • https://www.daolf.com/posts/best-programming-books/

  • https://codingwizardry.com/2020/11/13/10-best-books-for-programmers-in-2020/

  • 9 Must-Read Books for Software Engineers in 2023

    • “Build: An Unorthodox Guide to Making Things Worth Making” by Tony Fadell
      • is a must-read for anyone looking to create things that matter. Fadell shares his unique perspective on how to focus on small, achievable goals and pivot when necessary.
    • "The Phoenix Project: A Novel about IT, DevOps, and Helping Your Business Win” by Gene Kim, Kevin Behr, and George Spafford
      • is a captivating story about an IT manager who must turn around a failing project. Along the way, he learns about the principles of DevOps and how to apply them to his work.
    • “The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers” by Ben Horowitz
      • offers candid and practical advice on the challenges of entrepreneurship. Horowitz covers topics such as hiring, firing, and managing through tough times, and provides valuable insights on how to navigate the ups and downs of building a business.
    • “Structure and Interpretation of Computer Programs," also known as the “Wizard Book,”
      • is a classic text that covers the fundamental concepts of computer science and programming using the Lisp language. This book is a must-read for any serious software engineer.
    • "A Philosophy of Software Design” by John Ousterhout
      • argues that good software design is all about simplicity and clarity. He offers practical advice on how to achieve these qualities in your own code. This is a good one to read even on a yearly basis.
    • "The Pragmatic Programmer: From Journeyman to Master” by Andrew Hunt and David Thomas
      • is a comprehensive guide to becoming a better software engineer. It covers a wide range of topics, including debugging, testing, and refactoring, and is filled with useful tips and techniques. Make sure to pick up the 20th anniversary edition.
    • "An Elegant Puzzle: Systems of Engineering Management” by Will Larson
      • discusses the challenges and opportunities of managing software development teams. Larson covers topics such as building effective processes, setting goals, and creating a positive culture.
    • Software Engineering at Google: Lessons Learned from Programming Over Time” by Titus Winters, Tom Manshreck, and Hyrum Wright
      • offers a behind-the-scenes look at how Google approaches software development. It covers topics such as code review, testing, and technical debt, and provides valuable insights into how to build reliable and scalable systems.
    • INSPIRED: How to Create Tech Products Customers Love” by Marty Cagan
      • is a must-read for anyone looking to create successful tech products. Cagan covers topics such as defining the product vision, building a strong team, and gathering customer feedback, and provides practical advice on how to apply these principles to your own work. Commonly recommended for product managers, I think its a great read for engineers as well as it will help when working cross-functionally with your product team.

The must-read books in computer science

Some list I found a colleague forwarding

  1. The tree book (algorithms): Stein, Clifford., Rivest, Ronald L.., Cormen, Thomas H.., Leiserson, Charles E.. Introduction to Algorithms, Fourth Edition. United Kingdom: MIT Press, 2022.
  2. The cow book (databases): Ramakrishnan, Raghu., Gehrke, Johannes. Database Management Systems. United States: McGraw-Hill, 2000.
  3. The red book (databases) Michael Stonebraker, Joe Hellerstein. Readings in database systems. 5th edition. 2015. http://www.redbook.io/
  4. The dragon book(compilers) Alfred Aho, Jeffrey Ullman, Ravi Sethi, Monica Lam . Compilers: Principles, Techniques, and Tools. Second Edition. Pearson. 2006.
  5. The wizard book (logic) Gene Wolfe. The Wizard. Tor Fantasy. 2006.
  6. Cendrella book (automata theory) John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman. Introduction to automata theory, languages and computation. Pearson. 2006.
  7. The comet book (operating systems) Arpaci-Dusseau, Remzi H.., Arpaci-Dusseau, Andrea C.. Operating Systems: Three Easy Pieces. Germany: CreateSpace Independent Publishing Platform, 2018.
  8. Data mining Kamber, Micheline., Han, Jiawei., Pei, Jian. Data Mining: Concepts and Techniques. Netherlands: Elsevier Science, 2011.
  9. Deep learning Courville, Aaron., Bengio, Yoshua., Goodfellow, Ian. Deep Learning. United Kingdom: MIT Press, 2016.
  10. Reinforcement learning Barto, Andrew G.., Sutton, Richard S.. Reinforcement Learning: An Introduction. United Kingdom: MIT Press, 2018.