This book is based on the classic "Walls and Mirrors" approach used in the best-selling Data Abstraction and Problem Solving with C++, and is now updated to the Java programming language. It uses the running theme of "Walls and Mirrors" to help make clear the challenging concepts of recursion (the mirrors) and data abstraction (the walls). The authors cover key object-oriented concepts, including encapsulation, inheritance, and polymorphism; the focus of the book, however, remains on data abstraction. They also introduce the analysis of algorithms and Big "O" notation. For those who know a different language or who need a refresher, an appendix covering basic Java syntax is also provided. This book is appropriate for readers who are familiar with basic Java programming concepts or are new to the language and want to learn how it treats the concepts of recursion and data abstraction.

From the Back Cover:

Data Abstraction and Problem Solving in C++, and is now updated to the Java programming language. It uses the running theme of "Walls and Mirrors" to help make clear the challenging concepts of recursion (the mirrors) and data abstraction (the walls). Authors Carrano and Prichard cover key object-oriented concepts, including encapsulation, inheritance, and polymorphism. However, the focus of the book remains on data abstraction instead of simply Java syntax.

Features:

Provides a firm foundation in data abstraction (the walls), emphasizing the distinction between specification and implementation as the foundation for the object-oriented approach
Offers extensive coverage of recursion (the mirrors) and uses the technique throughout many examples and exercises.
Introduces analysis of algorithms and Big "O" notation.
Provides an appendix covering basic Java syntax for those know a different language or who need a refresher
Contains many pedagogical study aids such as programming pitfall warnings and self-tests with answers
A proven approach, adapted from the best selling Data Abstraction and Problem Solving in C++

0201702207B04062001

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