This exciting new data structures book provides students with powerful procedural programming skills that will serve as a solid foundation for later object-oriented programming. Throughout the book, Eric Roberts takes a library-based approach to the concepts, which allows readers to see more advanced programs early on. This innovative use of libraries will motivate students as they begin tackling more advanced data structures topics. In the first section of the book, Roberts brings readers up-to-speed on libraries and also provides a nice review of C. Eric Roberts is famous for his wonderful writing style, his use of real-world examples, and his special "bug features."

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Eric S.Roberts：Eric S.Roberts: 斯坦福大学计算机科学系教授，主管教学的系副主任。他由于教学改革的成就获得Charles Simonyi荣誉教授。Roberts于1980年获哈佛大学应用数学博士学位，其后他创建了威尔斯利学院的计算机科学系，并担任系主任。后来，他在加州Palo Alto的DEC公司系统研究中心工作了5年。

I. PRELIMINARIES.
1　An Overview of ANSI C.
　1.1 What is C
　1.2 The structure of a C program.
　1.3 Variables, values, and types.
　1.4 Expressions.
　1.5 Statements.
　1.6 Functions.
2　Data Types in C.
　2.1 Enumeration types.
　2.2 Data and memory.
　2.3 Pointers.
　2.4 Arrays.
　2.5 Pointers and arrays.
　2.6 Records.
　2.7 Dynamic allocation.
3　Libraries and Interfaces.
　3.1 The concept of an interface.
　3.2 Random numbers.
　3.3 Strings.
　3.4 The Standard I/O library.
　3.5 Other ANSI libraries.
II. RECURSION AND ALGORITHMIC ANALYSIS.
4　Introduction to Recursion.
　4.1 A simple example of recursion.
　4.2 The Factorial function.
　4.3 The Fibonacci function
　4.4 Other examples of recursion.
　4.5 Thinking recursively.
5　Recursive Procedures.
　5.1 The Towers of Hanoi.
　5.2 Generating permutations.
　5.3 Graphical applications of recursion.
6　Backtracing Algorithms.
　6.1 Solving a maze by recursive backtracking.
　6.2 Backtracking and games.
7　Analysis of Algorithms.
　7.1 The sorting problem.
　7.2 Computational complexity
　7.3 Recursion to the rescue.
　7.4 Standard complexity classes.
　7.5 The Quicksort algorithm.
　7.6 Mathematical induction.
III. DATA ABSTRACTION.
8　Abstract Data Types.
　8.1 Stacks.
　8.2 Defining a stack ADT.
　8.3 Using stacks in an application.
　8.4 Implementing the stack abstraction.
　8.5 Defining a scanner ADT.
9　Efficiency and ADTs.
　9.1 The concept of an editor buffer.
　9.2 Defining the buffer abstraction.
　9.3 Implementing the editor using arrays.
　9.4 Implementing the editor using stacks.
　9.5 Implementing the editor using linked lists.
10　Linear Structures: Stacks and Queues.
　10.1 Stacks revisited.
　10.2 Queues.
　10.3 Simulations involving queues.
11　Symbol Tables.
　11.1 Designing a symbol table abstraction.
　11.2 Hashing.
　11.3 Limitations of the preliminary interface
　11.4 Using functions as data.
　11.5 Mapping functions.
　11.6 Iterators.
　11.7 Command dispatch tables.
IV. RECURSIVE DATA.
12　Recursive Lists.
　12.1 The recursive formulation of a list.
　12.2 Defining an abstract list type.
　12.3 Using lists to represent large integers.
13　Trees.
　13.1 Family Trees.
　13.2 Binary search trees.
　13.3 Balanced trees.
　13.4 Defining a general interface for binary search trees.
14　Expression Trees.
　14.1 Overview of the interpreter.
　14.2 Understanding the abstract structure of rxpressions.
　14.3 Defining the concrete expression type.
　14.4 Parsing an expression.
　14.5 Evaluating an expression.
15　Sets.
　15.1 Sets as a mathematical abstraction.
　15.2 Designing a set interface.
　15.3 Implementing the set package.
　15.4 Designing a polymorphic iterator.
　15.5 Enhancing the efficiency of integer sets.
16　Graphs.
　16.1 The structure of a graph.
　16.2 Implementation strategies for graphs.
　16.3 Extending the graph abstraction.
　16.4 Graph traversals.
　16.5 Finding minimum paths.
17　Looking Ahead to Java.
　17.1 The object-Oriented paradigm.
　17.2 An introduction to Java .
　17.3 The structure of Java
　17.4 Predefined classes in Java
　17.5 Tools for creating interactive applets
INDEX