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How to Design Programs: An Introduction to Programming and Computing

   
지은이 Matthias Felleisen   |   출판사 MIT PRESS  |   발행일 2001년 02월 26일   |   언어 : English
 
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판매가 133,000원106,400원 20%
마일리지 1% 1,330원
발행일 2001-02-26 | 중량: 1.46 kg | 사이즈: 20.9*23.4*3.6 cm
ISBN 0262062186 |  9780262062183
기타정보 원서 | 720쪽 | $ 95 | Hardcover
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주식회사 도서출판인사이트 | Matthias Felleisen
 


This introduction to programming places computer science in the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process. This approach fosters a variety of skills--critical reading, analytical thinking, creative synthesis, and attention to detail--that are important for everyone, not just future computer programmers. The book exposes readers to two fundamentally new ideas. First, it presents program design guidelines that show the reader how to analyze a problem statement; how to formulate concise goals; how to make up examples; how to develop an outline of the solution, based on the analysis; how to finish the program; and how to test. Each step produces a well-defined intermediate product. Second, the book comes with a novel programming environment, the first one explicitly designed for beginners. The environment grows with the readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks. All the book's support materials are available for free on the Web. The Web site includes the environment, teacher guides, exercises for all levels, solutions, and additional projects.






I Processing Simple Forms of Data 3

1 Students, Teachers, and Computers 3
2 Numbers, Expressions, Simple Programs 5
3 Programs are Function Plus Variable Definitions 21
4 Conditional Expressions and Functions 29
5 Symbolic Information 46
6 Compound Data, Part 1: Structures 51
7 The Varieties of Data 79
Intermezzo 1: Syntax and Semantics 97

II Processing Arbitrarily Large Data 117
9 Compound Data, Part 2: Lists 117
10 More on Processing Lists 137
11 Natural Numbers 153
12 Composing Functions, Revisited Again 168
Intermezzo 2: List Abbreviations 183

III More on Processing Arbitrarily Large Data 189
14 More Self-referential Data Definitions 189
15 Mutually Referential Data Definitions 209
16 Development through Iterative Refinement 221
17 Processing Two Complex Pieces of Data 228
Intermezzo 3: Local Definitions and Lexical Scope 259

IV Abstracting Designs 283
19 Similarities in Definitions 283
20 Functions are Values 299
21 Designing Abstractions from Examples 306
22 Designing Abstractions with First-Class Functions 319
23 Mathematical Examples 334
Intermezzo 4: Defining Functions on the Fly 350

V Generative Recursion 357
25 A New Form of Recursion 357
26 Designing Algorithms 368
27 Variations on a Theme 381
28 Algorithms that Backtrack 406
Intermezzo 5: The Cost of Computing and Vectors 417

VI Accumulating Knowledge 441
30 The Loss of Knowledge 441
31 Designing Accumulator-Style Functions 450
32 More Uses of Accumulation 466
Intermezzo 6: The Nature of Inexact Numbers 478

VII Changing the State of Variables 491
34 Memory for Functions 491
35 Assignment to Variables 496
36 Designing Functions with Memory 507
37 Examples of Memory Usage 521
Intermezzo 7: The Final Syntax and Semantics 548

VIII Changing Compound Values 573
39 Encapsulation 573
40 Mutable Structures 587
41 Designing Functions that Change Structures 608
42 Equality 637
43 Changing Structures, Vectors, and Objects 642
Epilogue 677
Index 683

Matthias Felleisen is Professor of Computer Science at Rice University. He is the coauthor of A Little Java, A Few Patterns (MIT Press, 1998), The Little MLer (MIT Press, 1998), The Little Schemer (MIT Press, fourth edition, 1996), and The Seasoned Schemer (MIT Press, 1996). Robert Bruce Findler is a Ph.D. candidate in Computer Science at Rice University. Matthew Flatt is Assistant Professor in the School of Computing at the University of Utah. Shriram Krishnamurthi is Assistant Professor of Computer Science at Brown University.


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