《How to Think About Algorithms》PDF电子书下载
《How to Think About Algorithms》内容简介
Jeff Edmonds / Cambridge University Press / 2008-05-19 / USD 38.99 -
HOW TO THINK ABOUT ALGORITHMS
There are many algorithm texts that provide lots of well-polished code and
proofs of correctness. Instead, this one presents insights, notations, and
analogies to help the novice describe and think about algorithms like an
expert. It is a bit like a carpenter studying hammers instead of houses. Jeff
Edmonds provides both the big picture and easy step-by-step methods for
developing algorithms, while avoiding the comon pitfalls. Paradigms such
as loop invariants and recursion help to unify a huge range of algorithms
into a few meta-algorithms. Part of the goal is to teach students to think
abstractly. Without getting bogged down in formal proofs, the book fosters
deeper understanding so that how and why each algorithm works is trans-
parent. These insights are presented in a slow and clear manner accessible
to second- or third-year students of computer science, preparing them to
find on their own innovative ways to solve problems.
Abstraction is when you translate the equations, the rules, and the under-
lying essences of the problem not only into a language that can be commu-
nicated to your friend standing with you on a streetcar, but also into a form
that can percolate down and dwell in your subconscious. Because, remem-
ber, it is your subconscious that makes the miraculous leaps of inspiration,
not your plodding perspiration and not your cocky logic. And remember,
unlike you, your subconscious does not understand Java code.
Bookmarks
Cover
Half-title
Title
Copyright
CONTENTS
PREFACE
Introduction
PART ONE: Iterative Algorithms and Loop Invariants
1 Iterative Algorithms: Measures of Progress and Loop Invariants
1.1 A Paradigm Shift: A Sequence of Actions vs. a Sequence of Assertions
1.2 The Steps to Develop an Iterative Algorithm
1.3 More about the Steps
1.4 Different Types of Iterative Algorithms
1.5 Typical Errors
1.6 Exercises
HOW TO THINK ABOUT ALGORITHMS
There are many algorithm texts that provide lots of well-polished code and
proofs of correctness. Instead, this one presents insights, notations, and
analogies to help the novice describe and think about algorithms like an
expert. It is a bit like a carpenter studying hammers instead of houses. Jeff
Edmonds provides both the big picture and easy step-by-step methods for
developing algorithms, while avoiding the comon pitfalls. Paradigms such
as loop invariants and recursion help to unify a huge range of algorithms
into a few meta-algorithms. Part of the goal is to teach students to think
abstractly. Without getting bogged down in formal proofs, the book fosters
deeper understanding so that how and why each algorithm works is trans-
parent. These insights are presented in a slow and clear manner accessible
to second- or third-year students of computer science, preparing them to
find on their own innovative ways to solve problems.
Abstraction is when you translate the equations, the rules, and the under-
lying essences of the problem not only into a language that can be commu-
nicated to your friend standing with you on a streetcar, but also into a form
that can percolate down and dwell in your subconscious. Because, remem-
ber, it is your subconscious that makes the miraculous leaps of inspiration,
not your plodding perspiration and not your cocky logic. And remember,
unlike you, your subconscious does not understand Java code.
Bookmarks
Cover
Half-title
Title
Copyright
CONTENTS
PREFACE
Introduction
PART ONE: Iterative Algorithms and Loop Invariants
1 Iterative Algorithms: Measures of Progress and Loop Invariants
1.1 A Paradigm Shift: A Sequence of Actions vs. a Sequence of Assertions
1.2 The Steps to Develop an Iterative Algorithm
1.3 More about the Steps
1.4 Different Types of Iterative Algorithms
1.5 Typical Errors
1.6 Exercises
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