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Foundations of Computer Science in C. (Principles of Computer Science Series) Hardcover – 15 Oct 1994
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Top customer reviews
But there's more. After these two years I've collected many other books in various areas of CS, but when I need a quick reference on any specific topic or I don't remember the formal definition of a concept, I always find this book in my hands. It is one of the references I use most often.
It has been my first book by the couple Aho-Ullman. Now I've understood that whenever these two "emeritus guys" writes something, it always worths time and money to read them.
The book was written based on Stanford uni course notes from the course CS109 - Introduction to Computer Science and is really meant as a way to provide a solid foundation for further study.
Here's a chapter list
#1 Computer Science: The Mechanization of Abstraction
#2 Iteration, Induction and Recursion
#3 The Running Time of Programs
#4 Data Models for the Computer
#5 The Tree Data Model
#6 The List Data Model
#7 The Set Data Model
#8 The Relational Data Model
#9 The Graph Data Model
#10 Patterns, Automata and Regular Expressions
#11 Recursive Description of Patterns
#12 Propositional Logic
#13 Using Logic to Design Computer Components
#14 Predicate Logic
Most helpful customer reviews on Amazon.com
The book provides numerous examples and mathematical background for recursion, iteration, algorithmic efficiency, combinatorics and probability, as well as the major data structures.
I think if you take the time to go through this book you'll be well rewarded.
I then went with "Algorithms in C" by Sedgewick. There is depth there, but still verbose. In most cases this book's a great reference when I'm stuck understanding something in "The Art of Computer Programming". There are few proofs in "Algorithms in C". I know Sedgewick is world-class though, and that he's "dumbed down" his "algorithms" books; so much content regarding some topics is omitted, and the explanations are usually missing a lot. I know this because Sedgewick's definitions usually contain much less information than Knuth's when discussing topics both cover. His other two books are highly proof-based and outstanding, but neither deal explicitly with C. ("Analytic Combinatorics" and "An Introduction to the Analysis of Algorithms".)
This book is a perfect blend of theory and implementation. The reader is introduced to inductive proofs, predicate logic, regular expressions, probability, combinatorics, etc.After purchasing or perusing many other introductory programming books, this is the best one. None of the contemporary introductory programming books I've browsed through match the depth or breadth of this book. Not even close. It's great to see programs written by masters, too. Both Ullman and Aho are pioneers in this field, and it's great fun to see how they approach problem solving and programming!
This isn't a math book. Not by any stretch of the imagination. It contains useful, fundamental mathematical proof techniques and discusses mathematical concepts and their relation to programming. Any "programmers" or future computer scientists should be disabused of the fallacy that math isn't important in programming or computer science. It is a mathematical discipline, founded primarily by mathematicians and logicians. God forbid you're expected to be slightly mathematically competent.
Ullman and Aho's other books are great as well, and this one is no exception. It is without doubt the best introductory book that combines useful, relevant theory with corresponding implementations.