Design Theory and Computer Science

Cover......Page 1
Frontmatter......Page 2
Contents......Page 10
Preface......Page 14
Acknowledgements......Page 20
Part I - The Architectonics of Design......Page 22
1 - The Inadequacy of Definitions......Page 24
2.1 Demarcating engineering from science......Page 27
2.2 The matter of values......Page 30
3 - The Nature of Design Problems......Page 34
3.1 Empirical requirements......Page 35
3.2 Conceptual requirements......Page 49
3.3 The impreciseness of design problems......Page 51
3.4 Bounded rationality and the incompleteness of design problems......Page 53
3.5 Summary......Page 56
4.1 Designs as blueprints......Page 57
4.2 Designs as user guides......Page 70
4.3 Designs as media for criticism and change......Page 76
4.4 Summary......Page 79
5.1 The satisficing nature of design decisions......Page 83
5.2 The intractability of design optimization problems......Page 87
5.3 Design as an evolutionary process......Page 98
5.4 Empirical evidence of evolution in design......Page 102
5.5 Ontogenic and phylogenic design evolution......Page 134
5.6 Empirical evidence of evolution in phylogenic design......Page 136
Part II - Design Paradigms......Page 152
6.1 Introduction......Page 154
6.2 Kuhnian paradigms......Page 155
6.3 Defining the design paradigm concept......Page 162
6.4 Design paradigms in computer science......Page 163
7.1 Characteristics......Page 166
7.2 Some instances of ASE-based design methods......Page 168
7.3 Inductivism as the logical foundation for ASE......Page 179
7.4 Limitations of the ASE paradigm......Page 181
7.5 Remarks on requirements engineering......Page 190
7.6 The use of conceptual models......Page 191
7.7 Summary......Page 201
8.1 Designs as formal entities......Page 203
8.2 The formal approach in programming......Page 204
8.3 Hoare logic......Page 205
8.4 The formal development of programs......Page 214
8.5 The FD paradigm in computer architecture......Page 221
8.6 The formal design of microprograms......Page 231
8.7 The formal design of hardware structures......Page 238
8.8 Limits to the universality of formal design......Page 247
8.9 On the distinction between proofs of design correctness and mathematical proofs......Page 249
9.1 Introduction......Page 254
9.2 Constraints......Page 255
9.3 The plausibility of a constraint......Page 259
9.4 Plausibility states......Page 260
9.5 The nature of evidence in TPD......Page 261
9.6 Plausibility statements......Page 262
9.7 The logic of plausibility states......Page 265
9.8 The structure of plausibility-driven design......Page 270
9.9 Justification constraints......Page 273
9.10 Exercises in plausibility-driven design......Page 274
9.11 Discussion, contrasts and comparisons......Page 293
10.1 The automation of design......Page 298
10.2 General structure of the AI design paradigm......Page 299
10.3 Representing knowledge using production rules......Page 301
10.4 Thought experiments in rule-based design......Page 306
10.5 Weak methods revisited......Page 319
10.6 Multiple goal resolution......Page 328
10.7 The notion of style as a knowledge type......Page 331
10.8 The TPD paradigm revisited......Page 343
11.2 Compiling as an algorithmic style......Page 345
11.3 Knowledge representation in the algorithmic paradigm......Page 352
11.4 Algorithmic translation......Page 356
11.5 Algorithmic transformation......Page 363
11.6 The issue of `real\' optimization......Page 370
11.7 Conclusions......Page 371
Part III - Design and Science......Page 372
12.1 Introduction......Page 374
12.2 A reference model of science......Page 375
12.3 Two examples of scientific discoveries from physics......Page 381
12.4 The DSD model......Page 386
12.5 Two thought experiments......Page 392
12.6 On the richness of designs-as-theories......Page 396
12.7 Conclusions......Page 400
References......Page 402
Index......Page 436