Discrete Mathematics and Functional Programming
Franklin, Beedle & Associates Inc (Verlag)
978-1-59028-260-1 (ISBN)
- Titel nicht im Sortiment
- Artikel merken
This book provides a distinct way to teach discrete mathematics. Since discrete mathematics is crucial for rigorous study in computer science, many texts include applications of mathematical topics to computer science or have selected topics of particular interest to computer science. This text fully integrates discrete mathematics with programming and other foundational ideas in computer science.
In fact, this text serves not only the purpose of teaching discrete math. It is also an introduction to programming, although a non-traditional one. Functional programming is a paradigm in which the primary language construct is the function - and function here is essentially the same as what it is in mathematics. In the functional paradigm we conceive the program as a collection of composed functions, as opposed to a sequence of instructions (in the imperative paradigm) or a set of interacting objects (in the object-oriented paradigm). Dominant computer science curricula emphasize object-oriented and imperative programming, but competence in all paradigms is important for serious programmers - and functional programming in particular may be appropriate for many casual programmers, too. For our purposes, the concepts underlying functional programming are especially grounded in those of discrete mathematics.
Discrete mathematics and functional programming are equal partners in this endeavour, with the programming topics giving concrete applications and illustrations of the mathematical topics, and the mathematics providing the scaolding for explaining the programming concepts. The two work together in mutual illumination.
Chapter 1 Foundations 1.1 Your mathematical biography 1.2 Reasoning about items collectively 1.3 Set notation 1.4 Set operations 1.5 Verifying facts about sets 1.6 Values, expressions, and types in ML 1.7 Characters and strings 1.8 Cardinality, disjointness, and partitions 1.9 Cartesian products 1.10 Making your own types 1.11 Making your own operations 1.12 Recursive functions 1.13 Statements and exceptions 1.14 Extended example: A cumulative song 1.15 Special topic: Comparison with object-oriented programming Chapter 2 List 2.1 Lists 2.2 Functions on lists 2.3 Datatypes that use lists 2.4 Powersets 2.5 Case expressions and option types 2.6 Extended example: A language processor 2.7 Special topic: Lists vs. tuples vs. arrays Chapter 3 Proposition 3.1 Forms 3.2 Symbols 3.3 Boolean values 3.4 Logical equivalence 3.5 Conditional propositions 3.6 Conditionals and natural language 3.7 Conditional expressions 3.8 Arguments 3.9 Using argument forms for deduction 3.10 Predicates 3.11 Quantification 3.12 Multiple quantifi cation 3.13 Quantifi cation and algorithms 3.14 Quantifi cation and arguments 3.15 Extended example: Verifying arguments automatically 3.16 Special topic: Quantifi cation and natural language Chapter 4 Proof 4.1 General outline 4.2 Subset proofs 4.3 Set equality 4.4 Set emptiness 4.5 Conditional proofs 4.6 Integers 4.7 Biconditionals 4.8 Warnings 4.9 Case study: Powersets 4.10 From theorems to algorithms 4.11 Extended example: Solving games 4.12 Special topic: Russell's paradox Chapter 5 Relation 5.1 Defi nition 5.2 Representation 5.3 Image, inverse, and composition 5.4 Properties of relations 5.5 Equivalence relations 5.6 Computing transitivity 5.7 Transitive closure 5.8 Partial orders 5.9 Comparability and topological sort 5.10 Extended example: Unifi cation and resolution 5.11 Special topic: Representing relations Chapter 6 Self Reference 6.1 Peano numbers 6.2 Trees 6.3 Mutual recursion 6.4 Structural induction 6.5 Mathematical induction 6.6 Mathematical induction on sets 6.7 Program correctness 6.8 Sorting 6.9 Iteration 6.10 Loop invariants 6.11 From theorems to algorithms, revisited 6.12 Extended example: Huff man encoding 6.13 Special topic: Recursion vs. iteration Chapter 7 Function 7.1 Defi nition 7.2 Function equality 7.3 Functions as fi rst-class values 7.4 Images and inverse images 7.5 Map 7.6 Function properties 7.7 Inverse functions 7.8 Function composition 7.9 Cardinality 7.10 Counting 7.11 Permutations and combinations 7.12 Currying 7.13 Fixed-point iteration 7.14 Extended example: Modeling mathematical functions 7.15 Special topic: Countability Chapter 8 Graph 8.1 Defi nition and terms 8.2 Propositions on graphs 8.3 Strolling about a graph 8.4 Isomorphisms 8.5 A garden of graphs 8.6 Representing graphs 8.7 Extended example: Graph algorithms 8.8 Special topic: Graph coloring Chapter 9 Complexity Class 9.1 Recurrence relations 9.2 Complexity of algorithms 9.3 Analyzing sorting algorithms 9.4 Alternative examples of analyzing algorithms 9.5 Big-oh complexity classes 9.6 Big-theta and family 9.7 Properties of complexity classes 9.8 Tables 9.9 Memoization 9.10 Extended example: The Knapsack Problem 9.11 Special topic: P vs NP Chapter 10 Lattice 10.1 Defi nition and terms 10.2 Propositions on lattices 10.3 Isomorphisms 10.4 Modular and distributive lattices 10.5 Implementing lattice operations 10.6 Boolean algebras 10.7 Special topic: Digital logic circuits Chapter 11 Group 11.1 Preliminary terms 11.2 Defi nition 11.3 Isomorphisms 11.4 Subgroups 11.5 A garden of groups 11.6 Extended example: RSA encryption Chapter 12 Automaton 12.1 Alphabets and languages 12.2 Deterministic fi nite automata 12.3 Nondeterminism 12.4 Regular expressions 12.5 Language model equivalence and limitations 12.6 Context-free grammars 12.7 Push-down automata 12.8 The lambda calculus 12.9 Hierarchies of computational models 12.10 Special topic: Computability Appendix A Patterns for proofs
| Sprache | englisch |
|---|---|
| Maße | 190 x 235 mm |
| Gewicht | 1220 g |
| Themenwelt | Informatik ► Software Entwicklung ► Objektorientierung |
| Mathematik / Informatik ► Mathematik | |
| ISBN-10 | 1-59028-260-4 / 1590282604 |
| ISBN-13 | 978-1-59028-260-1 / 9781590282601 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
