Data Structures, Algorithms, and Software Principles in C

Häftad, Engelska, 1996

3 496 kr

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Beskrivning

Using C, this book develops the concepts and theory of data structures and algorithm analysis in a gradual, step-by-step manner, proceeding from concrete examples to abstract principles. Standish covers a wide range of both traditional and contemporary software engineering topics. The text also includes an introduction to object-oriented programming using C++. By introducing recurring themes such as levels of abstraction, recursion, efficiency, representation and trade-offs, the author unifies the material throughout. Mathematical foundations can be incorporated at a variety of depths, allowing the appropriate amount of math for each user.

Produktinformation

Utgivningsdatum:1996-01-07
Mått:200 x 230 x 42 mm
Vikt:1 400 g
Format:Häftad
Språk:Engelska
Antal sidor:768
Upplaga:1
Förlag:Pearson Education
ISBN:9780201591187

Utforska kategorier

Programmeringsböcker inom Data och IT
Systemvetenskap och AI inom Data och IT

Mer om författaren

Thomas A. Standish is the chairman of computer science at the University of California, Irvine. In 1990-91, he became the fourth winner of University of California Irvine's Distinguished Faculty Lectureship for Teaching, the campus' highest distinction for teaching excellence. He has also been a co-winner of his department's best-teacher award, chosen by the popular vote of University of California Irvine undergraduate computer science students. 0201591189AB04062001

Innehållsförteckning

( All chapters, except Chapter 1, begin with an Introduction and Motivation.) 1. Preparing for the Journey. Where Are We Going? Blending Mathematics, Science, and Engineering. The Search for Enduring Principles in Computer Science. Principles of Software System Structure. Efficiency and Tradeoffs. Software Engineering Principles. Our Approach to Mathematics. Some Notes on Programming Notation. Preview of Coming Attractions. 2. Linked Data Representations. What are Pointers? The Basic Intuition. Pointers in C—The Rudiments. Pointer Diagramming Notation. Linear Linked Lists. Other Linked Data Structures. 3. Introduction to Recursion. Thinking Recursively. Common Pitfall—Infinite Regresses. Quantitative Aspects of Recursive Algorithms. 4. Modularity and Data Abstraction. The Structure of C Modules. Priority Queues—An Abstract Data Type. A Pocket Calculator Interface. How to Hide Data Representations. Modularity and Information Hiding in Program Design. 5. Introduction to Software Engineering Concepts. Top-Down Programming By Stepwise Refinement. Proving Programs Correct. Transforming and Optimizing Programs. Testing Programs. The Philosophy of Measurement and Tuning. Software Reuse and Bottom-up Programming. Program Structuring and Documentation. 6. Introduction to Analysis of Algorithms. What Do We Use for a Yardstick? The Intuition Behind O-Notation. O-Notation—Definition and Manipulation. Analyzing Simple Algorithms. What O-Notation Doesn’t Tell You. 7. Linear Data Structures—Stacks and Queues. Some Background on Stacks. ADTs for Stacks and Queues. Using the Stack ADT to Check for Balanced Parentheses. Using the Stack ADT to Evaluate Postfix Expressions. Implementing the Stack ADT. How C Implements Recursive Function Calls Using Stacks. Implementations of the Queue ADT. More Queue Applications. 8. Lists, Strings, and Dynamic Memory Allocation. Lists. Generalized Lists. Applications of Generalized Lists. Strings. Dynamic Memory Allocation. 9. Trees. Basic Concepts and Terminology. Binary Trees. A Sequential Binary Tree Representation. An Application—Heaps and Priority Queues. Traversing Binary Trees. Binary Search Trees. AVL Trees and Their Performance. Two-Three Trees. Tries. An Application—Huffman Codes. 10. Graphs. Basic Concepts and Terminology. Graph Representations. Graph Searching. Topological Ordering. Shortest Paths. Task Networks. Useful Background on Graphs. 11. Hashing and the Table ADT. The Table ADT. Introduction to Hashing by Simple Examples. Collisions, Load Factors, and Clusters. Algorithms for Hashing by Open Addressing. Choosing a Hash Function. Comparison of Searching Methods Using the Table ADT. 12. External Collections of Data. Characteristics of External Storage Devices. Techniques That Don’t Work Well. Techniques That Work Well. Information Retrieval and Databases. 13. Sorting. Laying Some Groundwork. Priority Queue Sorting Methods. Divide-and-Conquer Methods. Methods That Insert Keys and Keep Them Sorted. O(n) Methods—Address Calculation Sorting. Other Methods. Comparison and Perspective. 14. Advanced Recursion. Recursion as a Descriptive Method. Using Recursion to Build a Parser. Translating from Infix to Postfix. Recursion and Program Verification. 15. Object-Oriented Programming. Exploring OOP Through Progressive Examples. Building Systems Using Object-Oriented Programming. Advantages and Disadvantages of Object-Oriented Programming. 16. Advanced Software Engineering Concepts. The Software Lifecycle. Software Productivity. Software Process Models. Appendix Math Reference and Tutorial. 0201591189T04062001