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Introduction to computation = Haskel...

Sannella, D.

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Introduction to computation = Haskell, logic and automata /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to computation/ by Donald Sannella ... [et al.].
其他題名:	Haskell, logic and automata /
其他作者:	Sannella, D.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	1 online resource (xvi, 366 p.) :ill. (some col.), digital ;24 cm.
內容註:	1. Sets -- 2. Types -- 3. Simple Computations -- 4. Venn Diagrams and Logical Connectives -- 5. Lists and Comprehensions -- 6. Features and Predicates -- 7. Testing Your Programs -- 8. Patterns of Reasoning -- 9. More Patterns of Reasoning -- 10. Lists and Recursion -- 11. More Fun with Recursion -- 12. Higher-Order Functions -- 13. Higher and Higher -- 14. Sequent Calculus -- 15. Algebraic Data Types -- 16. Expression Trees -- 17. Karnaugh Maps -- 18. Relations and Quantifiers -- 19. Checking Satisfiability -- 20. Data Representation -- 21. Data Abstraction -- 22. Efficient CNF Conversion -- 23. Counting Satisfying Valuations -- 24. Type Classes -- 25. Search in Trees -- 26. Combinatorial Algorithms -- 27. Finite Automata -- 28. Deterministic Finite Automata -- 29. Non-Deterministic Finite Automata -- 30. Input/Output and Monads -- 31. Regular Expressions -- 32 Non-Regular Languages -- Index.
Contained By:	Springer Nature eBook
標題:	Computer science - Mathematics. -
電子資源:	https://doi.org/10.1007/978-3-030-76908-6
ISBN:	9783030769086

Introduction to computation = Haskell, logic and automata /
Introduction to computationHaskell, logic and automata /[electronic resource] :by Donald Sannella ... [et al.]. - Cham :Springer International Publishing :2021. - 1 online resource (xvi, 366 p.) :ill. (some col.), digital ;24 cm. - Undergraduate topics in computer science,2197-1781. - Undergraduate topics in computer science..

1. Sets -- 2. Types -- 3. Simple Computations -- 4. Venn Diagrams and Logical Connectives -- 5. Lists and Comprehensions -- 6. Features and Predicates -- 7. Testing Your Programs -- 8. Patterns of Reasoning -- 9. More Patterns of Reasoning -- 10. Lists and Recursion -- 11. More Fun with Recursion -- 12. Higher-Order Functions -- 13. Higher and Higher -- 14. Sequent Calculus -- 15. Algebraic Data Types -- 16. Expression Trees -- 17. Karnaugh Maps -- 18. Relations and Quantifiers -- 19. Checking Satisfiability -- 20. Data Representation -- 21. Data Abstraction -- 22. Efficient CNF Conversion -- 23. Counting Satisfying Valuations -- 24. Type Classes -- 25. Search in Trees -- 26. Combinatorial Algorithms -- 27. Finite Automata -- 28. Deterministic Finite Automata -- 29. Non-Deterministic Finite Automata -- 30. Input/Output and Monads -- 31. Regular Expressions -- 32 Non-Regular Languages -- Index.

Computation is a process of calculation involving arithmetic and logical steps, following a given set of rules (an algorithm) This uniquely accessible textbook introduces students to computation using a very distinctive approach, quite rapidly leading them into essential topics with sufficient depth, yet in a highly intuitive manner. The work is anchored in coverage of functional programming (in Haskell), symbolic logic, and finite automata-- each a critical component of the foundations of Informatics, and together offering students a clear glimpse into an intellectual journey beyond mere mastery of technical skills. From core elements like types, Venn diagrams and logic, to patterns of reasoning, sequent calculus, recursion and algebraic data types, the book spans the breadth of key concepts and methods that will enable students to readily progress with their studies in Computer Science. Topics and features: Spans the key concepts and methods that underpin computation Develops symbolic logic, with a view toward honing clarity of thought; and automata, as a foundation for future study of both their applications and related theoretical topics Introduces powerful functional programming ideas that will be useful regardless which programming languages are used later Provides numerous exercises to support a clear and open, accessible approach Offers a dedicated website with resources for instructors and students, including code and links to online information Includes a wide array of marginal notes, empowering readers to "go beyond" the content presented Approaches logic and automata through Haskell code, to bring key concepts alive and foster understanding through experimentation Assuming no formal background in programming, this highly practical and accessible textbook provides the grounding fundamentals of computation for undergraduate students. Its flexible, yet clear expository style also makes the book eminently suitable as a self-study instructional guide for professionals or nonspecialists interested in these topics. Prof. Donald Sannella, Prof. Michael Fourman, and Prof. Philip Wadler are each at the University of Edinburgh's School of Informatics, Edinburgh, UK. Mr. Haoran Peng will soon pursue research interests in machine learning and machine intelligence at Cambridge University, Cambridge, UK.

ISBN: 9783030769086

Standard No.: 10.1007/978-3-030-76908-6doiSubjects--Topical Terms:

532725
Computer science
--Mathematics.

LC Class. No.: QA76.9.M35 / S36 2021

Dewey Class. No.: 004.0151

Introduction to computation = Haskell, logic and automata /
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505 0 $a 1. Sets -- 2. Types -- 3. Simple Computations -- 4. Venn Diagrams and Logical Connectives -- 5. Lists and Comprehensions -- 6. Features and Predicates -- 7. Testing Your Programs -- 8. Patterns of Reasoning -- 9. More Patterns of Reasoning -- 10. Lists and Recursion -- 11. More Fun with Recursion -- 12. Higher-Order Functions -- 13. Higher and Higher -- 14. Sequent Calculus -- 15. Algebraic Data Types -- 16. Expression Trees -- 17. Karnaugh Maps -- 18. Relations and Quantifiers -- 19. Checking Satisfiability -- 20. Data Representation -- 21. Data Abstraction -- 22. Efficient CNF Conversion -- 23. Counting Satisfying Valuations -- 24. Type Classes -- 25. Search in Trees -- 26. Combinatorial Algorithms -- 27. Finite Automata -- 28. Deterministic Finite Automata -- 29. Non-Deterministic Finite Automata -- 30. Input/Output and Monads -- 31. Regular Expressions -- 32 Non-Regular Languages -- Index.
520 $a Computation is a process of calculation involving arithmetic and logical steps, following a given set of rules (an algorithm) This uniquely accessible textbook introduces students to computation using a very distinctive approach, quite rapidly leading them into essential topics with sufficient depth, yet in a highly intuitive manner. The work is anchored in coverage of functional programming (in Haskell), symbolic logic, and finite automata-- each a critical component of the foundations of Informatics, and together offering students a clear glimpse into an intellectual journey beyond mere mastery of technical skills. From core elements like types, Venn diagrams and logic, to patterns of reasoning, sequent calculus, recursion and algebraic data types, the book spans the breadth of key concepts and methods that will enable students to readily progress with their studies in Computer Science. Topics and features: Spans the key concepts and methods that underpin computation Develops symbolic logic, with a view toward honing clarity of thought; and automata, as a foundation for future study of both their applications and related theoretical topics Introduces powerful functional programming ideas that will be useful regardless which programming languages are used later Provides numerous exercises to support a clear and open, accessible approach Offers a dedicated website with resources for instructors and students, including code and links to online information Includes a wide array of marginal notes, empowering readers to "go beyond" the content presented Approaches logic and automata through Haskell code, to bring key concepts alive and foster understanding through experimentation Assuming no formal background in programming, this highly practical and accessible textbook provides the grounding fundamentals of computation for undergraduate students. Its flexible, yet clear expository style also makes the book eminently suitable as a self-study instructional guide for professionals or nonspecialists interested in these topics. Prof. Donald Sannella, Prof. Michael Fourman, and Prof. Philip Wadler are each at the University of Edinburgh's School of Informatics, Edinburgh, UK. Mr. Haoran Peng will soon pursue research interests in machine learning and machine intelligence at Cambridge University, Cambridge, UK.
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