Customer Reviews

Models of Computation and Formal Languages

5 star:		(4)
4 star:		(0)
3 star:		(1)
2 star:		(0)
1 star:		(1)

 

 

The theory of computing can be a difficult subject to master, because of the densely symbolic notation and the mathematical complexity of the concepts. When I was a graduate student preparing for the theory portion of my exams, I remember being dismayed at the choice of textbooks that was available at the time: most simply threw a collection of Greek letters and subscripts at the reader, with little attempt to provide simply-worded explanations that would give the reader an intuition for the concepts.

Now that I am teaching the theory of computing, I want to provide my students with the best textbook I can find.

Two years ago, I was delighted to find R. Gregory Taylor's new book, "Models of Computation and Formal Languages". This is by far one of the most readable theory textbooks I have encountered. One of the features that caught my eye when I first examined the book was that many of the complicated symbolic expressions are accompanied by little explanatory text boxes with arrows that point to a symbol in the expression and explain the symbol that the arrow points to. I do this in class when I am lecturing -- I point to various symbols and explain where they came from, sometimes jotting down notes on the board alongside the symbols -- but this is the first time I have seen this technique in a textbook.

The writing style of the book is also fairly friendly and informal, without compromising mathematical precision.

The coverage of Turing-equivalent computing models is broader than in most introductory theory books; Taylor includes chapters not only on Turing Machines, but also on Recursive Function Theory, Markov Algorithms, Register Machines, Post Systems, and a model of parallel computation. Additionally, most chapters end with a proof that the model presented in that chapter is computationally equivalent to Turing Machines; thus, by the time the Church-Turing thesis is introduced in chapter 8, the reader is well prepared to entertain the claim that all of these models are capturing the same basic notion of an "algorithm".

I highly recommend this book to readers who want a readable introduction to computability theory.

I was a bit taken aback by the "reader from United States" who gave this book only one star. The subject is difficult so the book is difficult. The book is as readable as possible given the subject matter. As Albert E. once said, "As simple as possible, but no simpler". This book strikes that balance.

Basically, this book is not as good as for teaching use. I don't like the style of how the author state or arrange the topic. A lot confusion. But for those who have stronger math ground, it may be a not bad reference. The most point where I dispointed is the example or the solution of the excise is too abstract. The detailed induction, proof, explaination is especially importantant for beginner.So use this book as a reference.Don't choose as text book. Hard to follow!!!!

I read this book. This is an excellent book for understanding
a complex subject.

I have several books on this topic. This is the most excellent books along with animated software for each machine.

This book is being used as a text book in one of my graduate level classes. The book is dificult to read. It is down right torture to get through this book. This person obviously cannot write and needs to hire a technical writer to proof his work. The class is petitioning the professor to not use this book in the future. So I bought a $74 dollar paper weight.