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pp:2023:haskell:l07 [2023/04/19 22:11] tpruteanu [7.1 Lambda Calculus] |
pp:2023:haskell:l07 [2023/04/27 01:17] (current) mihai.udubasa [Lambda calculus as a programming language (optional)] fix typo |
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**A:** We can evaluate any of them, and it is guaranteed by [[https://en.wikipedia.org/wiki/Church%E2%80%93Rosser_theorem | Church-Rosser theorem]] that if the expression is reducible, we will eventually get the same $ \beta $**-normal form**. | **A:** We can evaluate any of them, and it is guaranteed by [[https://en.wikipedia.org/wiki/Church%E2%80%93Rosser_theorem | Church-Rosser theorem]] that if the expression is reducible, we will eventually get the same $ \beta $**-normal form**. | ||
- | To not just randomly choose **redexes**, there exist // reduction strategies //, from which we will use the **Normal Order** and **Applicative Order**: \\ | + | To not just randomly choose **redexes**, there exist //reduction strategies//, from which we will use the **Normal Order** and **Applicative Order**: \\ |
* **Normal Order** evaluation consist of always reducing the //leftmost//, //outermost// **redex** (whenever possible, subsitute the arguments into the function body) \\ | * **Normal Order** evaluation consist of always reducing the //leftmost//, //outermost// **redex** (whenever possible, subsitute the arguments into the function body) \\ | ||
* **Applicative Order** evaluation consist of always reducing the //leftmost//, //innermost// **redex** (always reduce the function argument before the function itself) \\ | * **Applicative Order** evaluation consist of always reducing the //leftmost//, //innermost// **redex** (always reduce the function argument before the function itself) \\ | ||
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- $ \lambda x.\lambda y.(x \ y \ x) \ \lambda x.\lambda y.x \ (\lambda x.\lambda y.\lambda z.(x \ z \ y) \ \lambda x.\lambda y.y)$ | - $ \lambda x.\lambda y.(x \ y \ x) \ \lambda x.\lambda y.x \ (\lambda x.\lambda y.\lambda z.(x \ z \ y) \ \lambda x.\lambda y.y)$ | ||
- $ \lambda x.y \ (\lambda x.(x \ x) \ \lambda x.(x \ x))$ | - $ \lambda x.y \ (\lambda x.(x \ x) \ \lambda x.(x \ x))$ | ||
- | ==== Booleans ==== | ||
- | We can encode boolean values **TRUE** and **FALSE** in lambda calculus as functions that take 2 values, **x** and **y**, and return the first (for **TRUE**) or second (for **FALSE**) value. \\ | ||
- | $ TRUE = \lambda x.\lambda y.y$ \\ | + | ==== Lambda calculus as a programming language (optional) ==== |
- | $ FALSE = \lambda x.\lambda y.x$ \\ | + | |
- | <note>As we defined it, **TRUE** is sometimes called the **K**-Combinator (or //Kestrel//), and **FALSE** the **KI**-Combinator (or //Kite//). </note> | + | The [[https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis | Church-Turing thesis]] asserts that any //computable// function can be computed using lambda calculus (or Turing Machines or equivalent models). \\ |
+ | For the curious, a series of additional exercises covering this topic can be found here: [[pp:2023:haskell:l07-extra|Lambda Calculus as a programming language]]. \\ | ||
- | <hidden> | + | ===== 7.2 Intro to Haskell ===== |
- | Some common operation on booleans (that were discussed during the lecture) are: \\ | + | |
- | \\ | + | |
- | $ AND = \lambda x.\lambda y.((x \ y) \ x) $ \\ | + | |
- | $ OR = \lambda x.\lambda y.((x \ x) \ y) $ \\ | + | |
- | $ NOT = \lambda x.((x \ FALSE) \ TRUE) $ \\ | + | |
- | <note> | + | **Prequisites**: having a working haskell environment ([[pp:haskell-environment|Haskell Environment]]) |
- | **NOT** can also be written as: \\ | + | |
- | \\ | + | |
- | $ NOT = \lambda x.\lambda a.\lambda b.((x \ b) \ a) $ \\ | + | |
- | \\ | + | |
- | You can convince yourself that this works by evaluating $ NOT \ TRUE $ and $ NOT \ FALSE $. This way of writting **NOT** is also called the **C**-Combinator (or //Cardinal//). | + | |
- | </note> | + | |
- | </hidden> | + | **Haskell** is a general-purpose, purely functional programming language, that we will use for the rest of the semester to showcase functional patterns and programming styles. \\ |
- | ==== Natural Numbers ==== | + | {{ :pp:2023:haskell:haskell.png?nolink&200 |}} |
- | Church numerals represent natural numbers as **higher-order functions**. Under this representation, the number //**n**// is a function that maps **f** to its **n-fold composition**. \\ | + | This section is designed for us to get comfortable with haskell syntax, we will use several concept that we learned in Scala, such as tail-recursion, folds and maps, but this time in a purely functional context. |
- | \\ | + | |
- | $ N0 = \lambda f.\lambda x. x $ \\ | + | |
- | $ N1 = \lambda f.\lambda x. (f \ x) $ \\ | + | |
- | $ N2 = \lambda f.\lambda x. (f \ (f \ x)) $ \\ | + | |
- | ... | + | |
- | <note> Does **N0** look familiar? It's the same as **FALSE** if you rename the variables (using $\alpha$-reduction). </note> | + | ==== A trip through time ==== |
+ | Remember: [[pp:2023:scala:l01|Lab 1. Introduction to Scala]] | ||
- | You can also define operation on church numerals, some (that were discussed during the lecture) are: \\ | + | **7.2.1.** Implement a tail-recursive function that computes the factorial of a natural number. |
- | \\ | + | <code haskell> |
- | $ SUCC = \lambda n.\lambda f.\lambda x.(f \ ((n \ f) \ x)) $ \\ | + | fact :: Int -> Int |
- | $ ISZERO = \lambda n.((n \lambda x.FALSE) \ TRUE) $ \\ | + | fact = undefined |
- | $ ADD = \lambda n.\lambda m.\lambda f.\lambda x.((n \ f) ((m \ f) \ x)) $ \\ | + | </code> |
- | \\ | + | **7.2.2.** Implement a tail-recursive function that computes the greatest common divisor of two natural numbers. |
- | **7.1.1** Define multiplication under church numerals: $ MULT = \lambda n.\lambda m. \ ... $ (without using the **Y**-combinator) | + | <code haskell> |
+ | mygcd :: Int -> Int -> Int | ||
+ | mygcd a b = undefined | ||
+ | </code> | ||
+ | **7.2.3.** Implement the function ''mySqrt'' which computes the square root of an integer $ a $. | ||
- | **7.1.2** Define exponentiation under church numerals: $ EXP = \lambda n.\lambda m. \ ... $ | + | ==== Lists ==== |
+ | The following Scala syntax for working with lists, can be translated to Haskell as follows: | ||
+ | ^ Scala ^ Haskell cases ^ Haskell pattern matching ^ Haskell guards ^ | ||
+ | |<code scala> | ||
+ | def f(l: List[Int]) = l match { | ||
+ | case Nil => ... | ||
+ | case (x::xs) => ... | ||
+ | } | ||
+ | </code>|<code haskell> | ||
+ | f l = case l of | ||
+ | [] -> ... | ||
+ | (x:xs) -> ... | ||
+ | </code> | <code haskell> | ||
+ | f [] = ... | ||
+ | f (x:xs) = ... | ||
+ | </code> | <code haskell> | ||
+ | f l | l == [] = ... | ||
+ | | otherwise = ... | ||
+ | </code> | | ||
- | **7.1.3** (*) Define the predecessor operator, that takes a number and returns the number prior to it. | + | **7.2.4.** Implement funtions ''mymin'' and ''mymax'' that take a list of ints, and return the smallest/biggest value in the list. |
- | What's the predecessor of 0? Evaluate $ PRED \ N0 $. | + | **7.2.5.** Implement a function ''unique'' that takes a list of ints, and removes all duplicates. |
+ | |||
+ | **7.2.6.** Given a list of ints, return a list of strings where for each element, return: | ||
+ | * **'Fizz'** if the number is divisible by 3 | ||
+ | * **'Buzz'** if the number is divisible by 5 | ||
+ | * **'FizzBuzz'** if the number is divisible by 3 **and** 5 | ||
+ | * a string representation of the number otherwise | ||
+ | |||
+ | **7.2.7.** Extend the function from **7.2.6.** with the following rules: | ||
+ | * **'Bazz'** if the number is divisible by 7 | ||
+ | * **'FizzBazz'** if the number is divisible by 21 | ||
+ | * **'BuzzBazz'** if the number is divisible by 35 | ||
+ | * **'FizzBuzzBazz'** if the number is divisible by 105 | ||
- | <hidden> | ||
- | $ PRED = \lambda n.\lambda f.\lambda x.(((n \ (\lambda g.\lambda h.h \ (g \ f))) \ (\lambda u.x)) \ (\lambda v.v)) $ \\ | ||
\\ | \\ | ||
- | $ \phi = \lambda p.PAIR \ (SND \ p) \ (SUCC \ (SND \ p)) $ \\ | + | <hidden> |
- | $ PRED = \lambda.n.FST \ (n \ \phi \ (PAIR \ N0 \ N0)) $ \\ | + | You can test **7.2.6.** and **7.2.7.** with the following snippet, if your function is $ f $: |
+ | <code haskell> | ||
+ | f [1..n] | ||
+ | </code> | ||
</hidden> | </hidden> | ||
- | \\ | + | <note> |
+ | In Haskell, the list data type is denote by the type the list holds surrounded by square paranthesis. | ||
+ | <code haskell> | ||
+ | [Int] -- list of ints | ||
+ | [Double] -- list of doubles | ||
+ | [[Int]] -- list of lists of ints (matrices) | ||
- | **7.1.4** Define substraction under church numerals: $ SUB = \lambda n.\lambda m. \ ... $ (**Hint**: use $ PRED $). | + | [] -- !!! not a data type, represents the empty list (Nil in Scala) |
+ | </code> | ||
+ | </note> | ||
- | What happens if you try to substract a bigger number from a smaller one? Evaluate $ SUB \ N1 \ N2 $. | + | ==== Types in Haskell ==== |
- | **7.1.5** Define $ LEQ $ (less or equal). $ LEQ \ n \ m $ should return **TRUE** if $ n \leq m $ and **FALSE** if $ n > m $. | + | In Haskell, functions are curried by default, **i.e.** a function: |
+ | <code haskell> | ||
+ | f a b = ... | ||
+ | </code> | ||
+ | is the same as: | ||
+ | <code haskell> | ||
+ | f = \a -> \b -> ... | ||
+ | </code> | ||
- | **7.1.6** Define $ EQ $ (equality). $ EQ \ n \ m $ should return **TRUE** if $ n = m $ and **FALSE** otherwise. | + | So, if $ a $ is a ''Int'' and $ b $ a ''Double'', and $ f $ returns a ''Char'', it would have the following type: |
+ | <code haskell> | ||
+ | f :: Int -> Double -> Char | ||
+ | </code> | ||
- | ===== 7.2 Recursion and the Y-Combinator ===== | + | **7.2.8.** Check the type signature of the following functions: |
+ | * ''foldl'' | ||
+ | * ''foldr'' | ||
+ | * ''filter'' | ||
+ | * ''map'' | ||
- | In lambda calculus, recursion is achieved using the fixed-point combinator (or **Y** combinator). \\ | + | <note important> |
- | A fixed-point combinator is a **higher-order** function that returns some fixed point of it's argument function (**x** is a fixed pointed for a function **f** if $ f(x) = x $). That means: $ f \ (fix \ f) = fix \ f $ \\ | + | If a function is not ambigous, ''ghc'' can infer the type signature, for **educational** purposes, going forward you will have to write signatures for all functions you define, this is considered good practice and helps prevent bugs. |
- | And by repeated application: $ fix \ f = f \ (f \ (... f \ (fix \ f)...)) $ \\ | + | </note> |
- | The **Y**-combinator in lambda calculus looks like this: \\ | + | |
- | \\ | + | <note tip> |
- | $ FIX = \lambda f.(\lambda x.f \ (x \ x)) (\lambda x.f \ (x \ x)) $ | + | In ''ghci'', you can check the type of a expression with: '':t'' |
- | \\ | + | </note> |
+ | |||
+ | ===== 7.3 Brain Twisters ===== | ||
+ | |||
+ | **7.3.1.** Implement ''map'' using ''foldl'' and ''foldr''. | ||
+ | <code haskell> | ||
+ | mymapl :: (a -> b) -> [a] -> [b] | ||
+ | mymapr :: (a -> b) -> [a] -> [b] | ||
+ | </code> | ||
+ | |||
+ | **7.3.2.** Implement ''filter'' using ''foldl'' and ''foldr''. | ||
+ | <code haskell> | ||
+ | myfilterl :: (a -> Bool) -> [a] -> [a] | ||
+ | myfilterr :: (a -> Bool) -> [a] -> [a] | ||
+ | </code> | ||
- | **7.2.1** Using the **Y**-Combinator, define a function that computes the factorial of a number **n**. | + | **7.3.3.** Implement ''foldl'' using ''foldr''. |
+ | <code haskell> | ||
+ | myfoldl :: (a -> b -> a) -> a -> [b] -> a | ||
+ | </code> | ||
- | **7.2.2** Using the **Y**-Combinator, define a function $ FIB $ that computes the **n**-th fibonacci number. | + | **7.3.4.** Implement ''bubbleSort''. |
+ | <code haskell> | ||
+ | bubbleSort :: [Int] -> [Int] | ||
+ | </code> | ||
- | ===== 7.3 Intro to Haskell ===== | + | **7.3.5.** Implement ''quickSort''. |
+ | <code haskell> | ||
+ | quickSort :: [Int] -> [Int] | ||
+ | </code> |