31 review for Classic Computer Science Problems in Java

1. 

   5 out of 5

   Xanan – Feb 10, 2021

   Reading this book will do no harm but ... The book discusses several algorithmic problems and illustrates how to solve them with Java. The code is reasonably simple to understand, well explained, and makes no use of external libraries. The author avoids math theory and formulas, making the book easy to follow for those who lack a mathematical background. This book is not addressed to Java beginners and is not a book on algorithms that explains Java along the way. Readers are supposed to already know Reading this book will do no harm but ... The book discusses several algorithmic problems and illustrates how to solve them with Java. The code is reasonably simple to understand, well explained, and makes no use of external libraries. The author avoids math theory and formulas, making the book easy to follow for those who lack a mathematical background. This book is not addressed to Java beginners and is not a book on algorithms that explains Java along the way. Readers are supposed to already know Java 8 (lambdas, streams and functional interfaces are used extensively besides collections and generics). Proposed solutions are often defined in terms of generic data types in order to make them applicable to a wider context than the motivational example. Almost always though, the proposed solutions rely on several simplifying assumptions or disregard details that may be important in a production environment. The book describes the basics of how to solve some classic problems in Java, so you can use is as a starting point to elaborate something more concrete that can be used in a real setting. However, for several problems discussed in the book, libraries exists that tackle that specific problem (the author notes that too). For instance, if you have to program a neural network, you will probably have to know some math (which the book does not provide), you will have to face some complexities that are not addressed in the book and, most important, rather than implement your own code you will want to rely on a library that was specifically developed for neural network programming, has been thoroughly tested and is widely accepted. More specific books that describe neural networks and the library are a better solution. This is true for other concepts discussed in the book, including graph algorithms, genetic algorithms, machine learning. The final chapter reports an interview by the author with Brian Goetz on his work as a Java architect. Sure, Goetz is a great Java guru and I greatly appreciated his concurrency book, but I did not expect to pay to read the transcript of one of his interviews. Those 14 pages could have been used for more on Java algorithms.

2. 

   5 out of 5

   Daniel Tanev –

3. 

   5 out of 5

   David Kopec – Feb 22, 2021

4. 

   4 out of 5

   Dowlath –

5. 

   5 out of 5

   César Laurenti –

6. 

   4 out of 5

   Onrooh –

7. 

   5 out of 5

   Derik –

8. 

   4 out of 5

   Miguel Paraz –

9. 

   4 out of 5

   Renanreismartins –

10. 

    5 out of 5

    Chukson –

11. 

    5 out of 5

    Petar –

12. 

    4 out of 5

    Svetlana –

13. 

    5 out of 5

    Łukasz Słonina –

14. 

    5 out of 5

    Karlo Novak –

15. 

    4 out of 5

    Brus –

16. 

    4 out of 5

    Nikola –

17. 

    4 out of 5

    Túlio Ribeiro dos Anjos –

18. 

    4 out of 5

    Eduard Kouts –

19. 

    4 out of 5

    Umut Salih –

20. 

    5 out of 5

    Martin –

21. 

    4 out of 5

    Onur Yurtsever –

22. 

    5 out of 5

    Byron Samson –

23. 

    4 out of 5

    Fahed Mohamedi –

24. 

    4 out of 5

    Tayná –

25. 

    4 out of 5

    Eddy –

26. 

    4 out of 5

    Scavazzini –

27. 

    4 out of 5

    Christopher Jaime –

28. 

    4 out of 5

    Balamurugan Krishnamoorthy –

29. 

    5 out of 5

    Mykola Rybak –

30. 

    5 out of 5

    Andrius Semionovas –

31. 

    4 out of 5

    Mishnagi –