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An introduction to the basic concepts on functional programming, explaining why it is a hot topic for some years now, what it is and some suggestions of functional languages to be learned.
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Why FP is a hot topic?
• Multicore CPUs
• VM based languages
• Great and easy to write DSLs
• Parsers
• Hardware design
• Expressiveness
What is it?
• Different programming paradigm
• OO
• Logic
• Procedural
• Functions are the main element in the language
Function applications“Functional programming is so called because a program consists entirely of functions. [...]
Typically the main function is defined in terms of other functions, which in turn are defined in terms of still more functions, until at the bottom level the functions are language primitives.”
John Hughes, 1989 - Why functional programming matters
OriginAlonzo Church developed Lambda
Calculus as part of his investigations on Math foundations
on 1936.
Lambda Calculus
• Variables
• Expressions (e1 e2)
• Lambda abstractions (λx. e)
Lambda Calculus (I)
• true = λxy. x
• false = λxy. y
• NOT a = (a)(false)(true)
• a AND b = (a)(b)(false)
• a OR b = (a)(true)(b)
• a XOR b = (a)((b)(false)(true))(b)
Basic concepts
• Pureness
• Pattern Matching
• Lazyness
• High Order Functions
• Currification (aka Partial Application)
Pureness
• No side-effects
• A function call can have no effect other than to compute its result
• Expressions can be evaluated at any time
• Programs are “referentially transparent”
Imperative stylefunction sum(elems: list of int) returns int {int total = 0;for elem in elems {total = total + elem;
}return total;
}
Imperative style
Computation method is variable assignment
function sum(elems: list of int) returns int {int total = 0;for elem in elems {total = total + elem;
}return total;
}
Functional stylePattern matching is cool!
Definition:sum [] = 0sum elem:rest = elem + sum rest
Application:sum [1,2,3,10]
Functional style
Computation method is function application
Definition:sum [] = 0sum elem:rest = elem + sum rest
Application:sum [1,2,3,10]
Lazyness
• aka “call by need”
• Expressions can be evaluated when necessary
• Allows the use of infinite lists
Lazyness (I)
Definition:even_numbers :: [Int]even_numbers = filter even [1..]
Application:take 5 even_numbers
Lazyness (II)
fibs :: [Int]fibs = 0 : 1 : zipWith (+) fibs (tail fibs)
From: http://en.wikipedia.org/wiki/Lazy_evaluation
High Order Functions
Functions which at least:
• Receive functions as parameters
• Return functions (aka curried functions)
High Order Functions (I)
map :: (a -> b) -> [a] -> [b]map f [] = []map f (x:xs) = f x : map f xs
Currification
sum :: Int -> Int -> Intsum x y = x + y
inc :: Int -> Intinc = sum 1
Where to go now?Suggestions:
• Haskell
• LISP
• Scheme
• Common LISP (CL)
• Clojure
• Erlang
• Scala
• F#
Haskell
• Pure n’ lazy
• Static typed
• Type classes
• Monads
• Lots of research & dev.
Haskell (I)
Freely available online:http://book.realworldhaskell.org/
LISP
• First functional language
• Lots of flavors
• Deal with parenthesis!
• Dynamic typed
• Homoiconic
Scheme
Freely available online:http://mitpress.mit.edu/sicp/
Clojure
• Runs on JVM
• Concurrency
Erlang
• Fault tolerant systems
• Concurrency
• Super easy!
• Dynamic typed
Scala
• Runs on JVM
• Several nice features
• Looks complex
• Static typed
F#
• Runs on .NET
• Result of MS’s investment on FP
• Simon Peyton Jones (Haskell contrib)
• Don Syme (F# creator)
• Erik Meijer (FP advocator, LINQ creator)
F# (I)
Pragmatic F# In Action
Josh Graham and Amanda Laucher
http://www.infoq.com/presentations/Pragmatic-F-Sharp-in-Action
Your Knowledge Portfolio
"Learn at least one new language every year. [...] Different languages solve the same problems in different ways. By learning several different approaches, you can help broaden your thinking and avoid getting stuck in a rut."
The Pragmatic Programmer
