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    Cover of A Common-Sense Guide to Data Structures and Algorithms

    A Common-Sense Guide to Data Structures and Algorithms

    Jay Wengrow · 2017

    If you last saw algorithms in a university course or at a job interview, you're missing out on what they can do for your code. Learn different sorting and searching techniques, and when to use each.

    Computer Science
    Open LibraryAmazon
    Stats for nerds
    9recommend
    14mentions
    11people
    2017–2025years
    86% recommend14% neutral

    Mentions per year

    201720182019202020212022202320242025

    What Hacker News says

    1. KerrickMar 2025
      Read books. Like, a lot of them.

      Start with Make It Stick (Brown et al.). Apply what this book teaches you to every one afterwards.

      Next, read and work through Exercises for Programmers (Hogan) and A Common Sense Guide to Data Structures and Algorithms (Wengrow).

      After you finish those two, read The Missing README (Riccomini et al.) and Extreme Programming Explained (Beck et al.). These two books provide very different viewpoints into the stuff that isn’t coding in a programming job.

      Assuming you’re using an OO language, follow that up with Object-Oriented Analysis and Design with Applications (Booch et al.) and Object Thinking. They contrast each other quite a bit; having both perspectives is handy.

      Once you’re through all those, I recommend Tidy First (Beck), Implementation Patterns (Beck), and Test-Driven Development By Example (Beck). These three books of his provide an incredibly accessible view into better ways to code.

      If you’re anything like me you get bored reading one book for too long. I’ve found that having a second book going that I can switch to is great for that. A parallel track with The Pattern On the Stone (Hillis), The Pragmatic Programmer (Thomas & Hunt), The Mythical Man-Month (Brooks), and How Computers Really Work (Justice) provides a reprieve and some technical and cultural context.

      thread
    2. rg111Aug 2023
      The author would do himself a great service if he chooses some other resource for learning algorithms.

      CLRS isn't bad. It is meant for a reference, and it also assumes that you are taking the course in college with an instructor teaching you.

      There are other great resources out there.

      Two I recommend are:

      - Algorithms, Coursera (Sedgewick, Wayne)

      - The Algorithm Design Manual (Skiena)

      I have recommended self-taught programmers in the past, which all of them liked:

      - A Common Sense Guide to Data Structures and Algorithms, PragProg (Jay Wengrow)

      - Algorithms Illumited, book or Coursera MOOC (Tim Rougharden)

      thread
    3. speakspokespokAug 2023
      I always recommend 'A Common Sense Guide to Data Structures and Algorithms' as well but I'd like to call out the 2nd edition has expanded the recursion chapters and in general the end of chapter assignments are better. The 2nd edition was born from several years of teaching material from the first edition.
      thread
    4. rg111May 2023
      After I passed a course and read other books on Algorithms, what really clicked Algorithms for me was this little known book: A Common Sense Guide to Data Structures and Algorithms by Jay Wengrow. This is what made Algorithms and Data Structures make sense to me.

      Later I read DPV and it was great, too.

      thread
    5. lannisterstarkMay 2023
      If you're a starter, I would heavily suggest A Common-Sense Guide to Data Structures and Algorithms by Jay Wengrow instead. It's written in a fantastic, easy to understand style and actually goes over everything as it explains it, both code examples and visualizations.

      https://pragprog.com/titles/jwdsal2/a-common-sense-guide-to-...

      thread
    6. speakspokespokJan 2023
      Thought the question was regarding specific books that teach programming via small projects it's worth mentioning a related topic here.

      A Common Sense Guide to Data Structures and Algorithms by Jay Wengrow * 2nd Edition * not only covers the theory really well but goes on to provide code examples in popular high level languages explaining when and how best to use them usefully. At the end of each section are prompts where you extend the lesson into a small project and each chapter builds on the last. The author has a github repo so you can compare your project solution to his. It made a rather dry topic extremely fun and approachable.

      thread

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