I want to make a new list that only contains the elements of the "list of lists" which have a length of 1.
The code that i provide gives a exception error: no function clause matching.
lists:foreach(fun(X) if length(X) =:= 1 -> [X] end, ListOfLists).
I am new to erlang, and I am having trouble finding an alternative way for writing this piece of code.
Can someone give me some advice on how to do so?
You can match in a list comprehension to get this quite naturally:
[L || L = [_] <- ListOfLists]
For example:
1> LoL = [[a], [b,c], d, [e], [f,g]].
[[a],[b,c],d,[e],[f,g]]
2> [L || L = [_] <- LoL].
[[a],[e]]
If you want the elements themselves (as in result [a, e] instead of [[a], [e]]) you can match on the element within the shape:
3> [L || [L] <- LoL].
[a,e]
Depending on the size of the lists contained within LoL, matching will be significantly faster than calling length/1 on every member. Calling length/1 and then testing the result requires traversing the entire list, returning a value, and then testing it. This is arbitrarily more overhead than checking if the second element of the list is a termination (in other words, if the "shape" of the data matches).
Regarding your attempt above...
As a newcomer to Erlang it might be helpful to become familiar with the basic functional list operations. They pop up over and over in functional (and logic) programming, and generally have the same names. "maps", "folds", "filters", "cons", "car" ("head" or "hd" or [X|_]), "cdr" ("tail" or "tl" or [_|X]), and so on.
Your original attempt:
lists:foreach(fun(X) if length(X) =:= 1 -> [X] end, ListOfLists).
This can't work because foreach/2 only returns ok, never any value. It is used only when you want to iterate over a list to get side-effects, not because you want to get a return value. For example, if I have a chat system the chat rooms have a list of current members, and broadcasting a message is really sending each chat message to each member in the list, I might do:
-spec broadcast(list(), unicode:chardata()) -> ok.
broadcast(Users, Message) ->
Forward = fun(User) -> send(User, Message) end,
lists:foreach(Forward, Users).
I don't care about the return value, really, and we aren't changing anything in the list Users or the Message. (Note that here we are using the anonymous function to capture the relevant state that it requires -- essentially currying out the Message value so we can present a function of arity 1 to the list operation foreach/2. This is where lambdas become most useful in Erlang vs named functions.)
When you want to take a list as an input and return a single, aggregate value (use some operation to roll all the values in the list into one) you can use a fold (you almost always want to use foldl/3, specifically):
4> lists:foldl(fun(X, A) when length(X) =:= 1 -> [X|A]; (_, A) -> A end, [], LoL).
[[e],[a]]
Broken down that reads as:
Single =
fun
(X, A) when length(X) =:= 1 -> [X|A];
(_, A) -> [X|A]
end,
ListOfSingles = lists:foldl(Single, [], LoL).
This is an anonymous function that has two clauses.
Written another way with a case we could do:
Single =
fun(X, A) ->
case length(X) of
1 -> [X|A];
_ -> A
end
end,
This is a matter of preference, as is the choice to inline that as an anonymous function within the call to foldl/3.
What you are really trying to do, though, is filter the list, and there is a universal list function called just that. You supply a testing function that returns a boolean -- if the test is true then the element will turn up in the output, otherwise it will not:
5> lists:filter(fun([X]) -> true; (_) -> false end, LoL).
[[a],[e]]
Breaking the lambda out as before:
6> Single =
6> fun([X]) -> true;
6> (_) -> false
6> end.
#Fun<erl_eval.6.54118792>
7> lists:filter(Single, LoL).
[[a],[e]]
Here we matched on the shape of the element in the anonymous function head. This filter is almost exactly equivalent to the list comprehension above (the only difference, really, is in the underlying implementation of list comprehensions -- semantically they are identical).
Related
I've written a function which search through a list of int-list to return the index of the list with an specific length by using pattern-matching:
let rec search x lst i = match lst with
| [] -> raise(Failure "Not found")
| hd :: tl -> if (List.length hd = x) then i else search x tl (i+1)
;;
For example:
utop # search 2 [ [1;2];[1;2;3] ] 0 ;;
- : int = 0
Is there a way to write a function with the same functionality using fold.left ?
What does List.fold_left actually do?
It takes (in reverse order to the order of arguments) a list, an initial value, and a function that works on that initial value and the first element in the list. If the list is empty, it returns the initial value. Otherwise it uses the function to update the initial value by way of recursion and works on the tail of the list.
let rec fold_left f init lst =
match lst with
| [] -> init
| x::xs -> fold_left f (f init x) xs
Now, what information do you need to keep track of as you iterate? The index. Easy enough.
But, what if you don't actually find a list of that length? You need to keep track of whether you've found one. So let's say we use a tuple of the index and a boolean flag.
Your function you pass to fold_left just needs to determine if a match has been found no update is necessary. Essentially we just no-op over the rest of the list. But, if we haven't found a match, then we need to test the current sublist's length and update the init value accordingly.
#glennsl (in a comment) and #Chris already explained that you may use List.fold_left but that it’s not the right tool for the job, because it processes the whole list whereas you want to stop once an occurrence is found. There are solutions but they are not satisfying:
(#Chris’ solution:) use a folding function that ignores the new elements once an occurrence has been found: you’re just wasting time, walking through the remaining tail for nothing;
evade the loop by throwing and catching an exception: better but hacky, you’re working around the normal functioning of List.fold_left.
I just mention that there is a generic function in the standard library that matches your situation almost perfectly:
val find : ('a -> bool) -> 'a list -> 'a
find f l returns the first element of the list l that satisfies the predicate f.
Raises Not_found if there is no value that satisfies f in the list l.
However it does not return the index, unlike what you are asking for. This is a deliberate design choice in the standard library, because list indexing is inefficient (linear time) and you shouldn’t do it. If, after these cautionary words, you still want the index, it is easy to write a generic function find_with_index.
Another remark on your code: you can avoid computing the lengths of inner lists fully, thanks to the following standard function:
val compare_length_with : 'a list -> int -> int
Compare the length of a list to an integer. compare_length_with l len is equivalent to compare (length l) len, except that the computation stops after at most len iterations on the list.
Since 4.05.0
So instead of if List.length hd = x, you can do if List.compare_length_with hd x = 0.
EDIT: see this followup question that simplifies the problem I am trying to identify here, and asks for input on a GHC modification proposal.
So I was trying to write a generic breadth-first search function and came up with the following:
bfs :: (a -> Bool) -> (a -> [a]) -> [a] -> Maybe a
bfs predf expandf xs = find predf bfsList
where bfsList = xs ++ concatMap expandf bfsList
which I thought was pretty elegant, however in the does-not-exist case it blocks forever.
After all the terms have been expanded to [], concatMap will never return another item, so concatMap is blocking waiting for another item from itself? Could Haskell be made smart enough to realize the list generation is blocked reading the self-reference and terminate the list?
The best replacement I've been able to come up with isn't quite as elegant, since I have to handle the termination case myself:
where bfsList = concat.takeWhile (not.null) $ iterate (concatMap expandf) xs
For concrete examples, the first search terminates with success, and the second one blocks:
bfs (==3) (\x -> if x<1 then [] else [x/2, x/5]) [5, 3*2**8]
bfs (==3) (\x -> if x<1 then [] else [x/2, x/5]) [5, 2**8]
Edited to add a note to explain my bfs' solution below.
The way your question is phrased ("could Haskell be made smart enough"), it sounds like you think the correct value for a computation like:
bfs (\x -> False) (\x -> []) []
given your original definition of bfs should be Nothing, and Haskell is just failing to find the correct answer.
However, the correct value for the above computation is bottom. Substituting the definition of bfs (and simplifying the [] ++ expression), the above computation is equal to:
find (\x -> False) bfsList
where bfsList = concatMap (\x -> []) bfsList
Evaluating find requires determining if bfsList is empty or not, so it must be forced to weak head normal form. This forcing requires evaluating the concatMap expression, which also must determine if bfsList is empty or not, forcing it to WHNF. This forcing loop implies bfsList is bottom, and therefore so is find.
Haskell could be smarter in detecting the loop and giving an error, but it would be incorrect to return [].
Ultimately, this is the same thing that happens with:
foo = case foo of [] -> []
which also loops infinitely. Haskell's semantics imply that this case construct must force foo, and forcing foo requires forcing foo, so the result is bottom. It's true that if we considered this definition an equation, then substituting foo = [] would "satisfy" it, but that's not how Haskell semantics work, for the same reason that:
bar = bar
does not have value 1 or "awesome", even though these values satisfy it as an "equation".
So, the answer to your question is, no, this behavior couldn't be changed so as to return an empty list without fundamentally changing Haskell semantics.
Also, as an alternative that looks pretty slick -- even with its explicit termination condition -- maybe consider:
bfs' :: (a -> Bool) -> (a -> [a]) -> [a] -> Maybe a
bfs' predf expandf = look
where look [] = Nothing
look xs = find predf xs <|> look (concatMap expandf xs)
This uses the Alternative instance for Maybe, which is really very straightforward:
Just x <|> ... -- yields `Just x`
Nothing <|> Just y -- yields `Just y`
Nothing <|> Nothing -- yields `Nothing` (doesn't happen above)
so look checks the current set of values xs with find, and if it fails and returns Nothing, it recursively looks in their expansions.
As a silly example that makes the termination condition look less explicit, here's its double-monad (Maybe in implicit Reader) version using listToMaybe as the terminator! (Not recommended in real code.)
bfs'' :: (a -> Bool) -> (a -> [a]) -> [a] -> Maybe a
bfs'' predf expandf = look
where look = listToMaybe *>* find predf *|* (look . concatMap expandf)
(*>*) = liftM2 (>>)
(*|*) = liftM2 (<|>)
infixl 1 *>*
infixl 3 *|*
How does this work? Well, it's a joke. As a hint, the definition of look is the same as:
where look xs = listToMaybe xs >>
(find predf xs <|> look (concatMap expandf xs))
We produce the results list (queue) in steps. On each step we consume what we have produced on the previous step. When the last expansion step added nothing, we stop:
bfs :: (a -> Bool) -> (a -> [a]) -> [a] -> Maybe a
bfs predf expandf xs = find predf queue
where
queue = xs ++ gen (length xs) queue -- start the queue with `xs`, and
gen 0 _ = [] -- when nothing in queue, stop;
gen n q = let next = concatMap expandf (take n q) -- take n elemts from queue,
in next ++ -- process, enqueue the results,
gen (length next) (drop n q) -- advance by `n` and continue
Thus we get
~> bfs (==3) (\x -> if x<1 then [] else [x/2, x/5]) [5, 3*2**8]
Just 3.0
~> bfs (==3) (\x -> if x<1 then [] else [x/2, x/5]) [5, 2**8]
Nothing
One potentially serious flow in this solution is that if any expandf step produces an infinite list of results, it will get stuck calculating its length, totally needlessly so.
In general, just introduce a counter and increment it by the length of solutions produced at each expansion step (length . concatMap expandf or something), decrementing by the amount that was consumed. When it reaches 0, do not attempt to consume anything anymore because there's nothing to consume at that point, and you should instead terminate.
This counter serves in effect as a pointer back into the queue being constructed. A value of n indicates that the place where the next result will be placed is n notches ahead of the place in the list from which the input is taken. 1 thus means that the next result is placed directly after the input value.
The following code can be found in Wikipedia's article about corecursion (search for "corecursive queue"):
data Tree a b = Leaf a | Branch b (Tree a b) (Tree a b)
bftrav :: Tree a b -> [Tree a b]
bftrav tree = queue
where
queue = tree : gen 1 queue -- have one value in queue from the start
gen 0 _ = []
gen len (Leaf _ : s) = gen (len-1) s -- consumed one, produced none
gen len (Branch _ l r : s) = l : r : gen (len+1) s -- consumed one, produced two
This technique is natural in Prolog with top-down list instantiation and logical variables which can be explicitly in a not-yet-set state. See also tailrecursion-modulo-cons.
gen in bfs can be re-written to be more incremental, which is usually a good thing to have:
gen 0 _ = []
gen n (y:ys) = let next = expandf y
in next ++ gen (n - 1 + length next) ys
bfsList is defined recursively, which is not in itself a problem in Haskell. It does, however, produce an infinite list, which, again, isn't in itself a problem, because Haskell is lazily evaluated.
As long as find eventually finds what it's looking for, it's not an issue that there's still an infinity of elements, because at that point evaluation stops (or, rather, moves on to do other things).
AFAICT, the problem in the second case is that the predicate is never matched, so bfsList just keeps producing new elements, and find keeps on looking.
After all the terms have been expanded to [] concatMap will never return another item
Are you sure that's the correct diagnosis? As far as I can tell, with the lambda expressions supplied above, each input element always expand to two new elements - never to []. The list is, however, infinite, so if the predicate goes unmatched, the function will evaluate forever.
Could Haskell be made smart enough to realize the list generation is blocked reading the self-reference and terminate the list?
It'd be nice if there was a general-purpose algorithm to determine whether or not a computation would eventually complete. Alas, as both Turing and Church (independently of each other) proved in 1936, such an algorithm can't exist. This is also known as the Halting problem. I'm not a mathematician, though, so I may be wrong, but I think it applies here as well...
The best replacement I've been able to come up with isn't quite as elegant
Not sure about that one... If I try to use it instead of the other definition of bfsList, it doesn't compile... Still, I don't think the problem is the empty list.
I have a list of lists like so:
[["BBBBBBBB",
"BWFFFPFGB",
"BWFFFPFGB",
"BWFFMPFGB",
"BWFFFPF_B",
"BWFFFPF6B",
"BBBBBBB"]]
I've done a little research and have found out how to access individual elements using the !! operator. But when it comes to searching for a certain element 'M' I'm not sure how to go about that. My friend said I need to use something like (x:xs):xss on a list, but when I try this in the WinGHCi haskell program I get this.
Prelude> let list = [["BBBBBBBB",
"BWFFFPFGB",
"BWFFFPFGB",
"BWFFMPFGB",
"BWFFFPF_B",
"BWFFFPF6B",
"BBBBBBB"]]
Prelude> head(x:xs):xss
<interactive>:192:2: Not in scope: `x'
<interactive>:192:4: Not in scope: `xs'
<interactive>:192:8: Not in scope: `xss'
I understand that I declare the name as list and not x:xs but even when I declare it as x:xs I still get the errors. I'm probably still a little new to haskell to really understand what to do so I may be going about this way wrong.
I've looked here Replace individual list elements in Haskell? because eventually I want to replace the M with something different but I'm not completely sure how I would implement that.
Any help/guidance is appreciated, thanks!
First let's see how to replace a W with M
charWM :: Char -> Char
charWM 'W' = 'M' -- If you see W, put M.
charWM x = x -- If you see anything else, put it back as is.
You can rewrite that function how you like by adding other letter transformations.
Now let's make that work over a list. There's a great function map :: (a ->b) -> [a] -> [b] that lets you apply a function on every element on a list.
stringWM :: String -> String
stringWM xs = map charWM xs -- do charWM to everything in xs.
For example stringWM "QWERTY WILL WIN" = "QMERTY MILL MIN"
Next we can do that to a list of lists:
lolWM :: [String] -> [String]
lolWM xss = map stringWM xss
(String is a type synonym for [Char].)
Let's test that out in ghci:
*Main> list'
["BBBBBBBB","BWFFFPFGB","BWFFFPFGB","BWFFMPFGB","BWFFFPF_B","BWFFFPF6B","BBBBBBB"]
*Main> lolWM list'
["BBBBBBBB","BMFFFPFGB","BMFFFPFGB","BMFFMPFGB","BMFFFPF_B","BMFFFPF6B","BBBBBBB"]
All good.
Your example wasn't exactly list', it was [list'] which has 1 element, so to work on that we'd need to map lolWM. Often we wouldn't bother writing stringWM or lolWM and go directly to lists of lists of lists, if that's what we needed:
lololWM = (map.map.map) charWM
map.map.map means map the map of the map. You can allow that to blow your mind a little, or you can just say list of list of list of Char, so map map map - one map per list level.
In the future, maybe you'll want to replace W with Strings instead of characters.
rewriteChar :: Char -> String
rewriteChar 'W' = "--^--"
rewriteChar x = [x] -- put x in a list to make it a string
This time, map isn't enough: map rewriteChar "QWERTY WILL WIN" gives
["Q","--^--","E","R","T","Y"," ","--^--","I","L","L"," ","--^--","I","N"]
We could use concat on that to flatten it into a single list, but it's more fun to do
rewriteString = concatMap rewriteChar
So now rewriteString "QWERTY WILL WIN" give us "Q--^--ERTY --^--ILL --^--IN".
For more mindblowing things to try, there's "QWERTY WILL WIN" >>= rewriteChar and "Hello Mum" >>= \x -> [x,x,x]
First of all, virtually all "variables" in Haskell are immutable, so there's no "changing a list", there are modified copies.
Second, you need to find an element by some criteria. To do that, you need to traverse a list. - This can be done using recursion. Filtering can be done using a function passed as an argument of your traversing function (this function must take an element and return a boolean value).
Try to put the above together and make your own function. Start with a type signature, it shows what you want to do: to take a list of Char (it's better to generalize to a generic type) and a function which possibly changes an element and return a modified list:
replaceFunc :: (Char -> Char) -> String -> String
Also, read http://www.haskell.org/haskellwiki/How_to_work_on_lists , there's a hint there how to apply some function to specific elements only.
I´m a newbie in SML and I´d like to update my function so that it has two outputs: a list AND 1 or 0. The function was proposed here: SML: Remove the entry from the List. It returns an updated list without a row that contains ´elem´.
fun removeElem elem myList = filter (fn x => x <> elem) myList
The function should return a new list AND 1, if a raw has been deleted. Otherwise, it should return an old list AND 0.
Any hint or example is highly appreciated. Thanks.
Note that all SML functions take a single input and return a single output. Instead, think of returning a tuple containing the new list and a flag indicating whether any elements were removed. One possibility is to use a couple of functions from the standard basis to test whether elem is in myList and build up a tuple consisting of that and the results from the filter shown in the question. The test might look like:
Option.isSome (List.find (fn x => x = elem) myList)
There are more concise ways to write that, but it shows the idea. Note that it returns a bool instead of an int; this is more precise, so I won't convert to the integers requested in the question.
A drawback of the above is that it requires traversing the list twice. To avoid that, consider the type that the function must return: a tuple of a list without elem and a flag showing whether any elems have been removed. We can then write a function that take a new value and a (valid) tuple, and returns a valid tuple. One possibility:
fun update(x, (acc, flag)) = if x = elem then (acc, true) else (x :: acc, flag)
We can then apply update to each element of myList one-by-one. Since we want the order of the list to stay the same, apart from the removed elements, we should work through myList from right to left, accumulating the results into an initially empty list. The function foldr will do this directly:
foldr update ([], false) myList
However, there is a lot of logic hidden in the foldr higher-order function.
To use this as a learning exercise, I'd suggest using this problem to implement the function in a few ways:
as a recursive function
as a tail-recursive function
using the higher order functions foldl and foldr
Understanding the differences between these versions will shed a lot of light on how SML works. For each version, let the types guide you.
As has been stated in some of your previous questions; Returning 0 or 1 as an indicator for what happened is a really bad design, as you don't get any guarantees from the types, whether or not you will get -42 as the result. Since you are working with a strongly typed language, you might as well use this to your advantage:
The most obvious thing to do instead would be to return a boolean, as that is actually what you are emulating with 0 and 1. In this case you could return the pair (true, modified_list) or (false, original_list).
Since you want to associate some data with the result, there is another -- perhaps, for some, less -- obvious thing to do; Return the result as an option, indication a change in the list as SOME modified_list and indication no change as NONE.
In either case you would have to "remember" whether or not you actually removed any elements from the original list, and thus you can't use the filter function. Instead you would have to do this for yourself using somewhat the same code as you originally posted.
One way would be like this
fun removeElem _ [] = (false, [])
| removeElem elem (x::xs) =
let
val (b, xs') = removeElem elem xs
in
if elem = x then
(true, xs')
else
(b, x::xs')
end
Another way would be to use a accumulator parameter to store the resulting list
fun removeElem elem xs =
let
fun removeElem' [] true res = SOME (rev res)
| removeElem' [] false _ = NONE
| removeElem' (x::xs) b res =
if elem = x then
removeElem' xs true res
else
removeElem' xs b (x::res)
in
removeElem' xs false []
end
Since the solution is being built in the reverse order, we reverse the result just before we return it. This makes sure that we don't have to use the costly append operation when adding elements to the result list: res # [x]
I've managed to get xUnit working on my little sample assembly. Now I want to see if I can grok FsCheck too. My problem is that I'm stumped when it comes to defining test properties for my functions.
Maybe I've just not got a good sample set of functions, but what would be good test properties for these functions, for example?
//transforms [1;2;3;4] into [(1,2);(3,4)]
pairs : 'a list -> ('a * 'a) list //'
//splits list into list of lists when predicate returns
// true for adjacent elements
splitOn : ('a -> 'a -> bool) -> 'a list -> 'a list list
//returns true if snd is bigger
sndBigger : ('a * 'a) -> bool (requires comparison)
There are already plenty of specific answers, so I'll try to give some general answers which might give you some ideas.
Inductive properties for recursive functions. For simple functions, this amounts probably to re-implementing the recursion. However, keep it simple: while the actual implementation more often than not evolves (e.g. it becomes tail-recursive, you add memoization,...) keep the property straightforward. The ==> property combinator usually comes in handy here. Your pairs function might make a good example.
Properties that hold over several functions in a module or type. This is usually the case when checking abstract data types. For example: adding an element to an array means that the array contains that element. This checks the consistency of Array.add and Array.contains.
Round trips: this is good for conversions (e.g. parsing, serialization) - generate an arbitrary representation, serialize it, deserialize it, check that it equals the original.
You may be able to do this with splitOn and concat.
General properties as sanity checks. Look for generally known properties that may hold - things like commutativity, associativity, idempotence (applying something twice does not change the result), reflexivity, etc. The idea here is more to exercise the function a bit - see if it does anything really weird.
As a general piece of advice, try not to make too big a deal out of it. For sndBigger, a good property would be:
let ``should return true if and only if snd is bigger`` (a:int) (b:int) =
sndBigger (a,b) = b > a
And that is probably exactly the implementation. Don't worry about it - sometimes a simple, old fashioned unit test is just what you need. No guilt necessary! :)
Maybe this link (by the Pex team) also gives some ideas.
I'll start with sndBigger - it is a very simple function, but you can write some properties that should hold about it. For example, what happens when you reverse the values in the tuple:
// Reversing values of the tuple negates the result
let swap (a, b) = (b, a)
let prop_sndBiggerSwap x =
sndBigger x = not (sndBigger (swap x))
// If two elements of the tuple are same, it should give 'false'
let prop_sndBiggerEq a =
sndBigger (a, a) = false
EDIT: This rule prop_sndBiggerSwap doesn't always hold (see comment by kvb). However the following should be correct:
// Reversing values of the tuple negates the result
let prop_sndBiggerSwap a b =
if a <> b then
let x = (a, b)
sndBigger x = not (sndBigger (swap x))
Regarding the pairs function, kvb already posted some good ideas. In addition, you could check that turning the transformed list back into a list of elements returns the original list (you'll need to handle the case when the input list is odd - depending on what the pairs function should do in this case):
let prop_pairsEq (x:_ list) =
if (x.Length%2 = 0) then
x |> pairs |> List.collect (fun (a, b) -> [a; b]) = x
else true
For splitOn, we can test similar thing - if you concatenate all the returned lists, it should give the original list (this doesn't verify the splitting behavior, but it is a good thing to start with - it at least guarantees that no elements will be lost).
let prop_splitOnEq f x =
x |> splitOn f |> List.concat = x
I'm not sure if FsCheck can handle this though (!) because the property takes a function as an argument (so it would need to generate "random functions"). If this doesn't work, you'll need to provide a couple of more specific properties with some handwritten function f. Next, implementing the check that f returns true for all adjacent pairs in the splitted lists (as kvb suggests) isn't actually that difficult:
let prop_splitOnAdjacentTrue f x =
x |> splitOn f
|> List.forall (fun l ->
l |> Seq.pairwise
|> Seq.forall (fun (a, b) -> f a b))
Probably the only last thing that you could check is that f returns false when you give it the last element from one list and the first element from the next list. The following isn't fully complete, but it shows the way to go:
let prop_splitOnOtherFalse f x =
x |> splitOn f
|> Seq.pairwise
|> Seq.forall (fun (a, b) -> lastElement a = firstElement b)
The last sample also shows that you should check whether the splitOn function can return an empty list as part of the returned list of results (because in that case, you couldn't find first/last element).
For some code (e.g. sndBigger), the implementation is so simple that any property will be at least as complex as the original code, so testing via FsCheck may not make sense. However, for the other two functions here are some things that you could check:
pairs
What's expected when the original length is not divisible by two? You could check for throwing an exception if that's the correct behavior.
List.map fst (pairs x) = evenEntries x and List.map snd (pairs x) = oddEntries x for simple functions evenEntries and oddEntries which you can write.
splitOn
If I understand your description of how the function is supposed to work, then you could check conditions like "For every list in the result of splitOn f l, no two consecutive entries satisfy f" and "Taking lists (l1,l2) from splitOn f l pairwise, f (last l1) (first l2) holds". Unfortunately, the logic here will probably be comparable in complexity to the implementation itself.