Note: this is the stubbed version of module Sum. Try to figure out how to fill in all parts of this file marked undefined. CIS 5520 students should be able to access this code through github. Eventually, the completed version will be available.

Optional exercise: foldr vs. foldl

This module contains some quick examples demonstrating the difference between foldr and foldl. It is advanced material for CIS 5520, designed for those who have seen fold and tail recursion before, such as in CIS 1200.

> module Sum where
> -- https://www.seas.upenn.edu/~cis5520/current/lectures/stub/02-higherorder/Sum.html
> 
> import Prelude hiding (foldr, foldl)

Let's start with a concrete example of a fold --- the "sum" function that adds together all numbers in a list. We can write this function in four different ways. The first two are the standard recursive definitions of sum. The third and fourth use a helper function that includes an accumulator.

> sum1 :: [Int] -> Int
> sum1 [] = 0
> sum1 (x:xs) = x + sum1 xs

> sum2 :: [Int] -> Int
> sum2 [] = 0
> sum2 (x:xs) = sum2 xs + x

> sum3 :: [Int] -> Int
> sum3 = sumAux 0  where
>    sumAux acc [] = acc 
>    sumAux acc (x : xs) = sumAux (acc + x) xs

> sum4 :: [Int] -> Int
> sum4 = sumAux 0  where
>    sumAux acc [] = acc 
>    sumAux acc (x : xs) = sumAux (x + acc) xs

All of these functions give us the same result because (+) is associative and commutative. However, none of these functions give us exactly the same computation: they each process the list in a different order.

     sum1 [1,2,3]
       == 1 + (2 + (3 + 0))
     sum2 [1,2,3]
       == ((0 + 3) + 2) + 1
     sum3 [1,2,3]
       == ((0 + 1) + 2) + 3
     sum4 [1,2,3]
       == (3 + (2 + (1 + 0)))

Generalizing Fold

We can generalize the examples above to create several different recursion patterns over lists. Compare these definitions with the variants of sum above. Then try to write the missing fourth variant`.

> -- | Generalization of recursion pattern in `sum1`
> foldr :: (a -> b -> b) -> b -> [a] -> b
> foldr f b = go where
>   go [] = b
>   go (x:xs) = x `f` go xs

> foldrFlip :: (b -> a -> b) -> b -> [a] -> b
> foldrFlip f b = go where
>   go [] = b
>   go (x:xs) = go xs `f` x

> foldl :: (b -> a -> b) -> b -> [a] -> b
> foldl f = go where
>   go acc [] = acc
>   go acc (x : xs) = go (acc `f` x) xs

> foldlFlip :: (a -> b -> b) -> b -> [a] -> b
> foldlFlip f = undefined

> sum1' :: [Int] -> Int
> sum1' = foldr (+) 0

> sum2' :: [Int] -> Int
> sum2' = foldrFlip (+) 0

> sum3' :: [Int] -> Int
> sum3' = foldl (+) 0

> sum4' :: [Int] -> Int
> sum4' = foldlFlip (+) 0

Now see what happens when you use these general operations with the (:) operator. Unlike (+), (:) is associative but not commutative so not all of the results will be the same.

> -- >>> foldr (:) [] [1,2,3]

> -- >>> foldrFlip (flip (:)) [] [1,2,3]

> -- >>> foldl (flip (:)) [] [1,2,3]

> -- >>> foldlFlip (:) [] [1,2,3]

On the other hand, the (-) operator is both not associative and not commutative, so again the results will be different.

> -- >>> foldr (-) 0 [1,2,3]

> -- >>> foldrFlip (-) 0 [1,2,3]

> -- >>> foldl (-) 0 [1,2,3]

> -- >>> foldlFlip (-) 0 [1,2,3]

Tail Recursion

Somewhat surprisingly, the definitions of sum3 and sum4 are not tail recursive. The problem is due to laziness: the argument in the recursive call to sumAux is not evaluated until the result is needed. To get an actual tail recursive function in Haskell, we need to evaluate this accumulator before sumAux is called recursively. Therefore, we will redefine sum4 using the operation ($!) which overrides laziness and forces call-by-value function application. In otherwords, with this operator, GHC will compile the code to evaluate the argument before making a recursiove call.

> sum5 :: [Int] -> Int
> sum5 = sumAux 0
>   where
>    sumAux acc [] = acc 
>    sumAux acc (x : xs) = (sumAux $! (x + acc)) xs

We can generalize this pattern by adding a strictness annotation to the definition of foldl. This is the definition of foldl' in the standard library.

> foldl' :: (b -> a -> b) -> b -> [a] -> b
> foldl' f = go  where
>   go acc [] = acc
>   go acc (x : xs) = (go $! acc `f` x) xs

Microbenchmarks

Here are some micro-benchmarks for thinking about laziness and saved computation.

If you would like to better understand the performance of various folds, you can use the :set +s command in GHCi to get timing and allocation information for each evaluation that you do.

To do so, first load the definitions in this module into GHCi. To do so, start the terminal in VS Code, and then use the command

  stack ghci Sum.hs

to start ghci and load the module.

Next, in GHCi you can type

Sum> :set +s

to cause GHCi to report timing and allocation data. If you make changes to any of the definitions in this file, you will need to reload it in ghci using the command

Sum> :r

For example, to compare the performance of the sum functions we can call them with large lists:

> c1, c2, c3, c4, c5 :: Int
> c1 = sum1 [1 .. 1000000]
> c2 = sum2 [1 .. 1000000]
> c3 = sum3 [1 .. 1000000]
> c4 = sum4 [1 .. 1000000]
> c5 = sum5 [1 .. 1000000]

When you ask GHCi to evaluate each of these computations, you will see both the timing and the number of bytes allocated.

    ghci> c1
    500000500000
    (0.38 secs, 226,778,360 bytes)

However, remember that GHC is lazy, so it will save the result. If you ask for the same value again, it will take much less time and space.

    ghci> c1
    500000500000
    (0.00 secs, 315,144 bytes)

Here are some other examples to try. What can you learn about Haskell's execution model from these examples?

> -- A potentially big computation
> h1 :: Int -> Int
> h1 y = sum1 [1 .. y * 100000]

> -- A potentially big computation (ignore first argument)
> f1 :: Int -> Int -> Int
> f1 _x y = sum1 [1 .. y * 100000]

> -- A potentially big computation (don't ignore first argument)
> g1 :: Int -> Int -> Int
> g1 x y = if x > 0 then sum1 [1 .. y * 100000] else sum2 [1 .. y * 100000]

> -- Call h1 with same argument multiple times.
> u1 :: Int
> u1 = h1 1 + h1 1 + h1 1

> -- Call f1 with same and different arguments multiple times.
> v1 :: Int
> v1 = f1 0 1 + f1 1 1 + f1 2 1
> v2 :: Int
> v2 = f1 0 1 + f1 0 1 + f1 0 1

> -- Call g1 with same and different arguments multiple times.
> w1 :: Int
> w1 = g1 0 1 + g1 1 1 + g1 2 1
> w2 :: Int
> w2 = g1 0 1 + g1 0 1 + g1 0 1

CIS 5520: Advanced Programming

Fall 2024

Optional exercise: foldr vs. foldl

Generalizing Fold

Tail Recursion

Microbenchmarks