Logo ČVUT
CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Functional Programming

The course is not on the list Without time-table
Code Completion Credits Range Language
BE4B36FUP Z,ZK 6 2P+2C
The course cannot be taken simultaneously with:
Functional Programming (B4B36FUP)
The course is a substitute for:
Functional Programming (B4B36FUP)
Lecturer:
Tutor:
Supervisor:
Department of Computer Science
Synopsis:

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.

Requirements:
Syllabus of lectures:

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

Syllabus of tutorials:
Study Objective:
Study materials:

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.

Note:
Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2019-10-18
For updated information see http://bilakniha.cvut.cz/en/predmet5148306.html