## Some Tricks for List Manipulation

This post is a collection of some of the tricks I’ve learned for manipulating lists in Haskell. Each one starts with a puzzle: you should try the puzzle yourself before seeing the solution!

# The Tortoise and the Hare

How can you split a list in half, in one pass, without taking its length?

This first one is a relatively well-known trick, but it occasionally comes in handy, so I thought I’d mention it. The naive way is as follows:

`= splitAt (length xs `div` 2) xs splitHalf xs `

But it’s unsatisfying: we have to traverse the list twice, and we’re taking its length (which is almost always a bad idea). Instead, we use the following function:

```
splitHalf :: [a] -> ([a],[a])
= go xs xs
splitHalf xs where
:ys) (_:_:zs) = first (y:) (go ys zs)
go (y= ([],ys) go ys _
```

The “tortoise and the hare” is the two arguments to `go`

: it traverses the second one twice as fast, so when it hits the end, we know that the first list must be halfway done.

# There and Back Again

Given two lists,

`xs`

and`ys`

, write a function which zips`xs`

with thereverseof`ys`

(in one pass).

There’s a lovely paper (Danvy and Goldberg 2005) which goes though a number of tricks for how to do certain list manipulations “in reverse”. Their technique is known as “there and back again”. However, I’d like to describe a different way to get to the same technique, using folds.

Whenever I need to do some list manipulation in reverse (i.e., I need the input list to be reversed), I first see if I can rewrite the function as a fold, and then just switch out `foldr`

for `foldl`

.

For our puzzle here, we need to first write `zip`

as a fold:

```
zip :: [a] -> [b] -> [(a,b)]
zip = foldr f b
where
:ys) = (x,y) : k ys
f x k (y= []
f x k [] = [] b _
```

If that looks complex, or difficult to write, don’t worry! There’s a systematic way to get to the above definition from the normal version of `zip`

. First, let’s start with a normal `zip`

:

```
zip :: [a] -> [b] -> [(a,b)]
zip [] ys = []
zip xs [] = []
zip (x:xs) (y:ys) = (x,y) : zip xs ys
```

Then, we need to turn it into a case-tree, where the first branch is on the list we want to fold over. In other words, we want the function to look like this:

```
zip xs = case xs of
???
```

To figure out the cases, we factor out the cases in the original function. Since the second clause (`zip xs [] = []`

) is only reachable when `xs /= []`

, it’s effectively a case for the `x:xs`

branch.

```
zip :: [a] -> [b] -> [(a,b)]
zip xs = case xs of
-> \_ -> []
[] :xs -> \case
x-> []
[] :ys -> (x,y) : zip xs ys y
```

Now, we rewrite the different cases to be auxiliary functions:

```
zip :: [a] -> [b] -> [(a,b)]
zip xs = case xs of
-> b
[] :xs -> f x xs
xwhere
= \_ -> []
b = \x xs -> \case
f -> []
[] :ys -> (x,y) : zip xs ys y
```

And finally, we *refactor* the recursive call to the first case expression.

```
zip :: [a] -> [b] -> [(a,b)]
zip xs = case xs of
-> b
[] :xs -> f x (zip xs)
xwhere
= \_ -> []
b = \x xs -> \case
f -> []
[] :ys -> (x,y) : xs ys y
```

Then those two auxiliary functions are what you pass to `foldr`

!

So, to reverse it, we simply take wherever we wrote `foldr f b`

, and replace it with `foldl (flip f) b`

:

```
zipRev :: [a] -> [b] -> [(a,b)]
= foldl (flip f) b
zipRev where
:ys) = (x,y) : k ys
f x k (y= []
f x k [] = [] b _
```

Of course, we’re reversing the wrong list here. Fixing that is simple:

```
zipRev :: [a] -> [b] -> [(a,b)]
= flip (foldl (flip f) b)
zipRev where
:xs) = (x,y) : k xs
f y k (x= []
f y k [] = [] b _
```

# Maintaining Laziness

Rewrite the above function without using continuations.

`zipRev`

, as written above, actually uses *continuation-passing style*. In most languages (including standard ML, which was the one used in Danvy and Goldberg (2005)), this is pretty much equivalent to a direct-style implementation (modulo some performance weirdness). In a lazy language like Haskell, though, continuation-passing style often makes things unnecessarily strict.

Consider the church-encoded pairs:

```
newtype Pair a b
= Pair
runPair :: forall c. (a -> b -> c) -> c
{
}
firstC :: (a -> a') -> Pair a b -> Pair a' b
= Pair (\k -> runPair p (k . f))
firstC f p
firstD :: (a -> a') -> (a, b) -> (a', b)
~(x,y) = (f x, y)
firstD f
fstD :: (a, b) -> a
~(x,y) = x
fstD
fstC :: Pair a b -> a
= runPair p const
fstC p
>>> fstC (firstC (const ()) undefined)
undefined
>>> fstD (firstD (const ()) undefined)
()
```

So it’s sometimes worth trying to avoid continuations if there is a fast direct-style solution. (alternatively, continuations can give you extra strictness when you *do* want it)

First, I’m going to write a different version of `zipRev`

, which folds on the first list, not the second.

```
= foldl f (\_ r -> r) xs ys []
zipRev xs ys where
:ys) r = k ys ((x,y):r) f k x (y
```

Then, we inline the definition of `foldl`

:

```
= foldr f id xs (\_ r -> r) ys []
zipRev xs ys where
= k (\(y:ys) r -> c ys ((x,y):r)) f x k c
```

Then, as a hint, we tuple up the two accumulating parameters:

```
= foldr f id xs snd (ys,[])
zipRev xs ys where
= k (\((y:ys),r) -> c (ys,(x,y):r)) f x k c
```

What we can see here is that we have two continuations stacked on top of each other. When this happens, they can often “cancel out”, like so:

```
= snd (foldr f (ys,[]) xs)
zipRev xs ys where
:ys,r) = (ys,(x,y):r) f x (y
```

And we have our direct-style implementation!

Note 14/05/2019: the “cancel-out” explanation there is a little handwavy, as I’m sure you’ll notice. However, there are a number of excellent explanations on this stackoverflow thread which explain it much better than I ever could. Thanks to Anders Kaseorg, Will Ness, user11228628, and to Joseph Sible (2019) for asking the question.

# Manual Fusion

Detect that a list is a palindrome, in one pass.

We now know a good way to split a list in two, and a good way to zip a list with its reverse. We can *combine* the two to get a program that checks if a list is a palindrome. Here’s a first attempt:

`= all (uncurry (==)) (uncurry zipRev (splitHalf xs)) isPal xs `

But this is doing *three* passes!

To get around it, we can manually do some fusion. Fusion is a technique where we can spot scenarios like the following:

`foldr f b (x : y : [])`

And translate them into a version without a list:

``f` (y `f` b) x `

The trick is making sure that the consumer is written as a fold, and then we just put its `f`

and `b`

in place of the `:`

and `[]`

in the producer.

So, when we inline the definition of `splitHalf`

into `zipRev`

, we get the following:

```
zipRevHalf :: [a] -> [(a,a)]
= snd (go xs xs)
zipRevHalf xs where
:ys) (_:_:zs) = f y (go ys zs)
go (y:ys) [_] = (ys,[])
go (_= (ys,[])
go ys []
:ys,r) = (ys,(x,y):r)
f x (y
= all (uncurry (==)) (zipRevHalf xs) isPal xs
```

(adding a special case for odd-length lists)

Finally, the `all (uncurry (==))`

is implemented as a fold also. So we can fuse it with the rest of the definitions:

```
isPal :: Eq a => [a] -> Bool
= snd (go xs xs)
isPal xs where
:ys) (_:_:zs) = f y (go ys zs)
go (y:ys) [_] = (ys,True)
go (_= (ys,True)
go ys []
:ys,r) = (ys,(x == y) && r) f x (y
```

You may have spotted the writer monad over `All`

there. Indeed, we can rewrite it to use the monadic bind:

```
isPal :: Eq a => [a] -> Bool
= getAll (fst (go xs xs)) where
isPal xs :ys) (_:_:zs) = f y =<< go ys zs
go (y:ys) [_] = pure ys
go (_= pure ys
go ys []
:zs) = (All (y == z), zs) f y (z
```

# Eliminating Multiple Passes with Laziness

Construct a Braun tree from a list in linear time.

This is also a very well-known trick (Bird 1984), but today I’m going to use it to write a function for constructing Braun trees.

A Braun tree is a peculiar structure. It’s a binary tree, where adjacent branches can differ in size by only 1. When used as an array, it has $\mathcal{O}(\log n)$ lookup times. It’s enumerated like so:

```
┌─7
┌3┤
│ └11
┌1┤
│ │ ┌─9
│ └5┤
│ └13
0┤
│ ┌─8
│ ┌4┤
│ │ └12
└2┤
│ ┌10
└6┤
└14
```

The objective is to construct a tree from a list in linear time, in the order defined above. Okasaki (1997) observed that, from the list:

`0..14] [`

Each level in the tree is constructed from chucks of powers of two. In other words:

`0],[1,2],[3,4,5,6],[7,8,9,10,11,12,13,14]] [[`

From this, we can write the following function:

```
= []
rows k [] = (k , take k xs) : rows (2*k) (drop k xs)
rows k xs
= zipWith3 Node xs ts1 ts2
build (k,xs) ts where
= splitAt k (ts ++ repeat Leaf)
(ts1,ts2)
= head . foldr build [Leaf] . rows 1 fromList
```

The first place we’ll look to eliminate a pass is the `build`

function. It combines two rows by splitting the second in half, and zipping it with the first.

```
>>> build (3, [x1,x2,x3]) [y1,y2,y3,y4,y5,y6]
[(x1,y1,y4),(x2,y2,y5),(x3,y3,y6)]
```

We don’t need to store the length of the first list, though, as we are only using it to split the second, and we can do *that* at the same time as the zipping.

```
zipUntil :: (a -> b -> c) -> [a] -> [b] -> ([c],[b])
= ([],ys)
zipUntil _ [] ys :xs) (y:ys) = first (f x y:) (zipUntil f xs ys)
zipUntil f (x
>>> zipUntil (,) [1,2] "abc"
1,'a'),(2,'b')],"c") ([(
```

Using this function in `build`

looks like the following:

```
= zipWith ($) ys ts2
build (k,xs) ts where
= zipUntil Node xs (ts ++ repeat Leaf) (ys,ts2)
```

That top-level `zipWith`

is *also* unnecessary, though. If we make the program circular, we can produce `ts2`

as we consume it, making the whole thing single-pass.

```
= ys
build xs ts where
= zip3Node xs (ts ++ repeat Leaf) ts2
(ys,ts2) :xs) (y:ys) ~(z:zs) = first (Node x y z:) (zip3Node xs ys zs)
zip3Node (x= ([], ys) zip3Node [] ys _
```

That `zip3Node`

is a good candidate for rewriting as a fold, also, making the whole thing look like this:

```
= []
rows k [] = take k xs : rows (2*k) (drop k xs)
rows k xs
= ys
build xs ts where
= foldr f b xs ts zs
(ys,zs) :ys) ~(z:zs) = first (Node x y z:) (xs ys zs)
f x xs (y= ([],ys)
b ys _
= head . foldr build (repeat Leaf) . rows 1 fromList
```

To fuse all of those definitions, we first will need to rewrite `rows`

as a fold:

```
= uncurry (:) (foldr f b xs 1 2)
rows xs where
= ([],[])
b _ _ 0 j = ([], uncurry (:) (f x k j (j*2)))
f x k = first (x:) (k (i-1) j) f x k i j
```

Once we have everything as a fold, the rest of the transformation is pretty mechanical. At the end of it all, we get the following linear-time function for constructing a Braun tree from a list:

```
fromList :: [a] -> Tree a
= head (l (foldr f b xs 1 2))
fromList xs where
= (repeat Leaf, (repeat Leaf, ys))
b _ _ ys zs
= let (xs, ys) = uncurry k ys in xs
l k
0 j ys zs = ([], (l (f x k j (j*2)), ys))
f x k ~(y:ys) ~(z:zs) = first (Node x y z:) (k (i-1) j ys zs) f x k i j
```

# References

Bird, R. S. 1984. “Using Circular Programs to Eliminate Multiple Traversals of Data.” *Acta Inf.* 21 (3) (October): 239–250. doi:10.1007/BF00264249. http://dx.doi.org/10.1007/BF00264249.

Danvy, Olivier, and Mayer Goldberg. 2005. “There and Back Again.” *BRICS Report Series* 12 (3). doi:10.7146/brics.v12i3.21869. https://tidsskrift.dk/brics/article/view/21869.

Okasaki, Chris. 1997. “Three Algorithms on Braun Trees.” *Journal of Functional Programming* 7 (6) (November): 661–666. doi:10.1017/S0956796897002876. https://www.eecs.northwestern.edu/~robby/courses/395-495-2013-fall/three-algorithms-on-braun-trees.pdf.

Sible, Joseph. 2019. “How Can Two Continuations Cancel Each Other Out?” *Stack Overflow*. https://stackoverflow.com/questions/56122022/how-can-two-continuations-cancel-each-other-out.