Cay Horstmann
Rance Necaise
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Cay Horstmann
San Jose State University
Rance Necaise
Randolph-Macon College
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10 9 8 7 6 5 4 3 2 1
This book is an introduction to computer programming using Python that focuses on
the essentials—and on effective learning. Designed to serve a wide range of student
interests and abilities, it is suitable for a first course in programming for computer
scientists, engineers, and students in other disciplines. No prior programming expe-
rience is required, and only a modest amount of high school algebra is needed. For
pedagogical reasons, the book uses Python 3, which is more regular than Python 2.
Here are the book’s key features:
Present fundamentals first.
The book takes a traditional route, first stressing control structures, functions,
procedural decomposition, and the built-in data structures. Objects are used when
appropriate in the early chapters. Students start designing and implementing their
own classes in Chapter 9.
Guidance and worked examples help students succeed.
Beginning programmers often ask “How do I start? Now what do I do?” Of course,
an activity as complex as programming cannot be reduced to cookbook-style
instructions. However, step-by-step guidance is immensely helpful for building con-
fidence and providing an outline for the task at hand. “Problem Solving” sections
stress the importance of design and planning. “How To” guides help students with
common programming tasks. Numerous “Worked Examples” demonstrate how to
apply chapter concepts to interesting problems.
Problem solving strategies are made explicit.
Practical, step-by-step illustrations of techniques help students devise and evaluate
solutions to programming problems. Introduced where they are most relevant, these
strategies address barriers to success for many students. Strategies included are:
•
Algorithm Design (with pseudocode)
•
First Do It By Hand (doing sample
calculations by hand)
•
Flowcharts
•
Test Cases
•
Hand-Tracing
•
Storyboards
•
Solve a Simpler Problem First
•
Reusable Functions
Practice makes perfect.
•
Stepwise Refinement
•
Adapting Algorithms
•
Discovering Algorithms by
Manipulating Physical Objects
•
Tracing Objects
•
Patterns for Object Data
•
Thinking Recursively
•
Estimating the Running Time of
an Algorithm
Of course, programming students need to be able to implement nontrivial programs,
but they first need to have the confidence that they can succeed. Each section con-
tains numerous exercises that as
k students to carry out progressively more complex
tasks: trace code and understand its effects, produce program snippets from prepared
parts, and complete simple programs. Additional review and programming problems
are provided at the end of each chapter.
iii
PREFACE
