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Explanatory Notes
Instructions
Web page:
https://cw.fel.cvut.cz/wiki/courses/fup/start
Anotation:
This course introduces students into the techniques of functional
programming, the advantages and disadvantages of this programming
paradigm, and its use in practice. This approach is declarative in the
sense that the programmer symbolically describes the problem to be
solved, rather than specifying the exact sequence of operations
required to solve it. It allows focusing on the essence of the solved
problem and implementing even more complex algorithms compactly.
Functional programming has notable advantages for parallelization and
automated verification of algorithms, and the most useful functional
programming concepts are increasingly often introduced to standard
programming languages. Because of the focus of functional programming
on symbols, rather than numbers, functional programming has been
heavily used in in artificial intelligence fields, such as agent
systems or symbolic machine learning.
This course is also part of the inter-university programme prg.ai Minor. It pools the best of AI education in Prague to provide students with a deeper and broader insight into the field of artificial intelligence. More information is available at
https://prg.ai/minor.
Course outlines:
| 1. | | Introduction to declarative programming languages. Comparison to |
classical imperative languages. Main principles and practical
applications of functional programming.
| 2. | | LISP: basic constructions of the language, atoms, lists, recursion |
| 3. | | LISP: basic language idioms, atoms, lists, recursion |
| 3. | | LISP: built-in functions, data structures, lambda abstraction |
| 4. | | LISP: built-in high-order functions |
| 5. | | LISP: infinite data structures, closures |
| 6. | | Introduction to Lambda calculus, relation to functional programming |
| 7. | | Equivalence of functional programming to Turing machine |
| 8. | | Types in functional languages, their role and consequences to the |
expressive power of the languages, typed Lambda calculus
| 9. | | Haskell: types, patterns, built-in functions, lambda abstraction |
| 10. | | Haskell: lazy evaluation, partial function application |
| 11. | | Haskell: monads |
| 12. | | Automated optimizations in functional programming, formal |
verification of functional programs
| 13. | | Functional programming and parallel computation |
| 14. | | Functional constructs in popular programming languages and tools |
Exercises outline:
Literature:
Hudak, Paul, and Joseph H. Fasel. "A gentle introduction to Haskell." ACM Sigplan Notices 27.5 (1992): 1-52.
Harvey, Brian, and Matthew Wright. Simply Scheme: introducing computer science. Mit Press, 1999.
Requirements:
Subject is included into these academic programs:
| Page updated 21.11.2024 09:52:34, semester: Z/2024-5, L/2023-4, Z/2025-6, L/2024-5, Send comments about the content to the Administrators of the Academic Programs |
Proposal and Realization: I. Halaška (K336), J. Novák (K336) |