[[!toc]]
-##Same-fringe using a zipper-based coroutine##
+Recall [[the recent homework assignment|/exercises/assignment12]] where you solved the same-fringe problem with a `make_fringe_enumerator` function, or in the Scheme version using streams instead of zippers, with a `lazy-flatten` function.
-Recall back in [[Assignment4]], we asked you to enumerate the "fringe" of a leaf-labeled tree. Both of these trees (here I *am* drawing the labels in the diagram):
-
- . .
- / \ / \
- . 3 1 .
- / \ / \
- 1 2 2 3
-
-have the same fringe: `[1; 2; 3]`. We also asked you to write a function that determined when two trees have the same fringe. The way you approached that back then was to enumerate each tree's fringe, and then compare the two lists for equality. Today, and then again in a later class, we'll encounter new ways to approach the problem of determining when two trees have the same fringe.
-
-
-Supposing you did work out an implementation of the tree zipper, then one way to determine whether two trees have the same fringe would be: go downwards (and leftwards) in each tree as far as possible. Compare the targetted leaves. If they're different, stop because the trees have different fringes. If they're the same, then for each tree, move rightward if possible; if it's not (because you're at the rightmost position in a sibling list), move upwards then try again to move rightwards. Repeat until you are able to move rightwards. Once you do move rightwards, go downwards (and leftwards) as far as possible. Then you'll be targetted on the next leaf in the tree's fringe. The operations it takes to get to "the next leaf" may be different for the two trees. For example, in these trees:
-
- . .
- / \ / \
- . 3 1 .
- / \ / \
- 1 2 2 3
-
-you won't move upwards at the same steps. Keep comparing "the next leaves" until they are different, or you exhaust the leaves of only one of the trees (then again the trees have different fringes), or you exhaust the leaves of both trees at the same time, without having found leaves with different labels. In this last case, the trees have the same fringe.
-
-If your trees are very big---say, millions of leaves---you can imagine how this would be quicker and more memory-efficient than traversing each tree to construct a list of its fringe, and then comparing the two lists so built to see if they're equal. For one thing, the zipper method can abort early if the fringes diverge early, without needing to traverse or build a list containing the rest of each tree's fringe.
-
-Let's sketch the implementation of this. We won't provide all the details for an implementation of the tree zipper, but we will sketch an interface for it.
-
-First, we define a type for leaf-labeled, binary trees:
-
- type 'a tree = Leaf of 'a | Node of ('a tree * 'a tree)
-
-Next, the interface for our tree zippers. We'll help ourselves to OCaml's **record types**. These are nothing more than tuples with a pretty interface. Instead of saying:
-
- # type blah = Blah of (int * int * (char -> bool));;
-
-and then having to remember which element in the triple was which:
-
- # let b1 = Blah (1, (fun c -> c = 'M'), 2);;
- Error: This expression has type int * (char -> bool) * int
- but an expression was expected of type int * int * (char -> bool)
- # (* damnit *)
- # let b1 = Blah (1, 2, (fun c -> c = 'M'));;
- val b1 : blah = Blah (1, 2, <fun>)
-
-records let you attach descriptive labels to the components of the tuple:
-
- # type blah_record = { height : int; weight : int; char_tester : char -> bool };;
- # let b2 = { height = 1; weight = 2; char_tester = (fun c -> c = 'M') };;
- val b2 : blah_record = {height = 1; weight = 2; char_tester = <fun>}
- # let b3 = { height = 1; char_tester = (fun c -> c = 'K'); weight = 3 };; (* also works *)
- val b3 : blah_record = {height = 1; weight = 3; char_tester = <fun>}
-
-These were the strategies to extract the components of an unlabeled tuple:
-
- let h = fst some_pair;; (* accessor functions fst and snd are only predefined for pairs *)
-
- let (h, w, test) = b1;; (* works for arbitrary tuples *)
-
- match b1 with
- | (h, w, test) -> ...;; (* same as preceding *)
-
-Here is how you can extract the components of a labeled record:
-
- let h = b2.height;; (* handy! *)
-
- let {height = h; weight = w; char_tester = test} = b2
- in (* go on to use h, w, and test ... *)
-
- match test with
- | {height = h; weight = w; char_tester = test} ->
- (* same as preceding *)
-
-Anyway, using record types, we might define the tree zipper interface like so:
-
- type 'a starred_level = Root | Starring_Left of 'a starred_nonroot | Starring_Right of 'a starred_nonroot
- and 'a starred_nonroot = { parent : 'a starred_level; sibling: 'a tree };;
-
- type 'a zipper = { level : 'a starred_level; filler: 'a tree };;
-
- let rec move_botleft (z : 'a zipper) : 'a zipper =
- (* returns z if the targetted node in z has no children *)
- (* else returns move_botleft (zipper which results from moving down and left in z) *)
-
-<!--
- let {level; filler} = z
- in match filler with
- | Leaf _ -> z
- | Node(left, right) ->
- let zdown = {level = Starring_Left {parent = level; sibling = right}; filler = left}
- in move_botleft zdown
- ;;
--->
-
- let rec move_right_or_up (z : 'a zipper) : 'a zipper option =
- (* if it's possible to move right in z, returns Some (the result of doing so) *)
- (* else if it's not possible to move any further up in z, returns None *)
- (* else returns move_right_or_up (result of moving up in z) *)
-
-<!--
- let {level; filler} = z
- in match level with
- | Starring_Left {parent; sibling = right} -> Some {level = Starring_Right {parent; sibling = filler}; filler = right}
- | Root -> None
- | Starring_Right {parent; sibling = left} ->
- let z' = {level = parent; filler = Node(left, filler)}
- in move_right_or_up z'
- ;;
--->
-
-The following function takes an `'a tree` and returns an `'a zipper` focused on its root:
-
- let new_zipper (t : 'a tree) : 'a zipper =
- {level = Root; filler = t}
- ;;
-
-Finally, we can use a mutable reference cell to define a function that enumerates a tree's fringe until it's exhausted:
-
- let make_fringe_enumerator (t: 'a tree) =
- (* create a zipper targetting the botleft of t *)
- let zbotleft = move_botleft (new_zipper t)
- (* create a refcell initially pointing to zbotleft *)
- in let zcell = ref (Some zbotleft)
- (* construct the next_leaf function *)
- in let next_leaf () : 'a option =
- match !zcell with
- | Some z -> (
- (* extract label of currently-targetted leaf *)
- let Leaf current = z.filler
- (* update zcell to point to next leaf, if there is one *)
- in let () = zcell := match move_right_or_up z with
- | None -> None
- | Some z' -> Some (move_botleft z')
- (* return saved label *)
- in Some current
- | None -> (* we've finished enumerating the fringe *)
- None
- )
- (* return the next_leaf function *)
- in next_leaf
- ;;
-
-Here's an example of `make_fringe_enumerator` in action:
-
- # let tree1 = Leaf 1;;
- val tree1 : int tree = Leaf 1
- # let next1 = make_fringe_enumerator tree1;;
- val next1 : unit -> int option = <fun>
- # next1 ();;
- - : int option = Some 1
- # next1 ();;
- - : int option = None
- # next1 ();;
- - : int option = None
- # let tree2 = Node (Node (Leaf 1, Leaf 2), Leaf 3);;
- val tree2 : int tree = Node (Node (Leaf 1, Leaf 2), Leaf 3)
- # let next2 = make_fringe_enumerator tree2;;
- val next2 : unit -> int option = <fun>
- # next2 ();;
- - : int option = Some 1
- # next2 ();;
- - : int option = Some 2
- # next2 ();;
- - : int option = Some 3
- # next2 ();;
- - : int option = None
- # next2 ();;
- - : int option = None
-
-You might think of it like this: `make_fringe_enumerator` returns a little subprogram that will keep returning the next leaf in a tree's fringe, in the form `Some ...`, until it gets to the end of the fringe. After that, it will keep returning `None`.
-
-Using these fringe enumerators, we can write our `same_fringe` function like this:
-
- let same_fringe (t1 : 'a tree) (t2 : 'a tree) : bool =
- let next1 = make_fringe_enumerator t1
- in let next2 = make_fringe_enumerator t2
- in let rec loop () : bool =
- match next1 (), next2 () with
- | Some a, Some b when a = b -> loop ()
- | None, None -> true
- | _ -> false
- in loop ()
- ;;
-
-The auxiliary `loop` function will keep calling itself recursively until a difference in the fringes has manifested itself---either because one fringe is exhausted before the other, or because the next leaves in the two fringes have different labels. If we get to the end of both fringes at the same time (`next1 (), next2 ()` matches the pattern `None, None`) then we've established that the trees do have the same fringe.
-
-The technique illustrated here with our fringe enumerators is a powerful and important one. It's an example of what's sometimes called **cooperative threading**. A "thread" is a subprogram that the main computation spawns off. Threads are called "cooperative" when the code of the main computation and the thread fixes when control passes back and forth between them. (When the code doesn't control this---for example, it's determined by the operating system or the hardware in ways that the programmer can't predict---that's called "preemptive threading.") Cooperative threads are also sometimes called *coroutines* or *generators*.
+The technique illustrated in those solutions is a powerful and important one. It's an example of what's sometimes called **cooperative threading**. A "thread" is a subprogram that the main computation spawns off. Threads are called "cooperative" when the code of the main computation and the thread fixes when control passes back and forth between them. (When the code doesn't control this---for example, it's determined by the operating system or the hardware in ways that the programmer can't predict---that's called "preemptive threading.") Cooperative threads are also sometimes called *coroutines* or *generators*.
With cooperative threads, one typically yields control to the thread, and then back again to the main program, multiple times. Here's the pattern in which that happens in our `same_fringe` function:
<!-- * [[!wikipedia Green_threads]]
* [[!wikipedia Protothreads]] -->
-The way we built cooperative threads here crucially relied on two heavyweight tools. First, it relied on our having a data structure (the tree zipper) capable of being a static snapshot of where we left off in the tree whose fringe we're enumerating. Second, it relied on our using mutable reference cells so that we could update what the current snapshot (that is, tree zipper) was, so that the next invocation of the `next_leaf` function could start up again where the previous invocation left off.
+The way we built cooperative threads using `make_fringe_enumerator` crucially relied on two heavyweight tools. First, it relied on our having a data structure (the tree zipper) capable of being a static snapshot of where we left off in the tree whose fringe we're enumerating. Second, it either required us to manually save and restore the thread's snapshotted state (a tree zipper); or else we had to use a mutable reference cell to save and restore that state for us. Using the saved state, the next invocation of the `next_leaf` function could start up again where the previous invocation left off.
+
+It's possible to build cooperative threads without using those tools, however. Already our [[solution using streams|/exercises/assignment12#streams2]] uses neither zippers nor any mutation. Instead it saves the thread's state in explicitly-created thunks, and resumes the thread by forcing the thunk.
-It's possible to build cooperative threads without using those tools, however. Some languages have a native syntax for them. Here's how we'd write the same-fringe solution above using native coroutines in the language Lua:
+Some languages have a native syntax for coroutines. Here's how we'd write the same-fringe solution above using native coroutines in the language Lua:
> function fringe_enumerator (tree)
if tree.leaf then
To get a better understanding of how that execution pattern works, we'll add yet a second execution pattern to our plate, and then think about what they have in common.
-While writing OCaml code, you've probably come across errors. In fact, you've probably come across errors of two sorts. One sort of error comes about when you've got syntax errors or type errors and the OCaml interpreter isn't even able to understand your code:
+While writing OCaml code, you've probably come across errors. In fact, you've probably come across errors of several sorts. One sort of error comes about when you've got syntax errors and the OCaml interpreter isn't even able to parse your code. A second sort of error is type errors, as in:
# let lst = [1; 2] in
"a" :: lst;;
Error: This expression has type int list
but an expression was expected of type string list
-But you may also have encountered other kinds of error, that arise while your program is running. For example:
+Type errors are also detected and reported before OCaml attempts to execute or evaluate your code. But you may also have encountered a third kind of error, that arises while your program is running. For example:
# 1/0;;
Exception: Division_by_zero.
# List.nth [1;2] 10;;
Exception: Failure "nth".
-These "Exceptions" are **run-time errors**. OCaml will automatically detect some of them, like when you attempt to divide by zero. Other exceptions are *raised* by code. For instance, here is the implementation of `List.nth`:
+These "Exceptions" are **run-time errors**. OCaml will automatically detect some of them, like when you attempt to divide by zero. Other exceptions are *raised* by code. For instance, here is the standard implementation of `List.nth`:
let nth l n =
if n < 0 then invalid_arg "List.nth" else
| a::l -> if n = 0 then a else nth_aux l (n-1)
in nth_aux l n
-Notice the two clauses `invalid_arg "List.nth"` and `failwith "nth"`. These are two helper functions which are shorthand for:
+(The Juli8 version of `List.nth` only differs in sometimes raising a different error.) Notice the two clauses `invalid_arg "List.nth"` and `failwith "nth"`. These are two helper functions which are shorthand for:
raise (Invalid_argument "List.nth");;
raise (Failure "nth");;
raise bad
-the effect is for the program to immediately stop. That's not exactly true. You can also programmatically arrange to *catch* errors, without the program necessarily stopping. In OCaml we do that with a `try ... with PATTERN -> ...` construct, analogous to the `match ... with PATTERN -> ...` construct:
+the effect is for the program to immediately stop. That's not exactly true. You can also programmatically arrange to *catch* errors, without the program necessarily stopping. In OCaml we do that with a `try ... with PATTERN -> ...` construct, analogous to the `match ... with PATTERN -> ...` construct. (In OCaml 4.02 and higher, there is also a more inclusive construct that combines these, `match ... with PATTERN -> ... | exception PATTERN -> ...`.)
# let foo x =
try
*and that exception is never caught*, then the effect is for the program to immediately stop.
-Trivia: what's the type of the `raise (Failure "two")` in:
+**Trivia**: what's the type of the `raise (Failure "two")` in:
if x = 1 then 10
else raise (Failure "two")
(fun x -> raise (Failure "two") : 'a -> 'a)
-Remind you of anything we discussed earlier? /Trivia.
+Remind you of anything we discussed earlier? (At one point earlier in term we were asking whether you could come up with any functions of type `'a -> 'a` other than the identity function.)
+
+**/Trivia.**
Of course, it's possible to handle errors in other ways too. There's no reason why the implementation of `List.nth` *had* to raise an exception. They might instead have returned `Some a` when the list had an nth member `a`, and `None` when it does not. But it's pedagogically useful for us to think about the exception-raising pattern now.
Here we call `foo bar 0`, and `foo` in turn calls `bar 0`, and `bar` raises the exception. Since there's no matching `try ... with ...` block in `bar`, we percolate back up the history of who called that function, and we find a matching `try ... with ...` block in `foo`. This catches the error and so then the `try ... with ...` block in `foo` (the code that called `bar` in the first place) will evaluate to `20`.
-OK, now this exception-handling apparatus does exemplify the second execution pattern we want to focus on. But it may bring it into clearer focus if we simplify the pattern even more. Imagine we could write code like this instead:
+OK, now this exception-handling apparatus does exemplify the second execution pattern we want to focus on. But it may bring it into clearer focus if we **simplify the pattern** even more. Imagine we could write code like this instead:
# let foo x =
try begin
else
return 20 -- abort early
end
- return value + 100 -- in Lua, a function's normal value
- -- must always also be explicitly returned
+ return value + 100 -- in a language like Scheme, you could omit the `return` here
+ -- but in Lua, a function's normal result must always be explicitly `return`ed
end
> return foo(1)
##What do these have in common?##
-In both of these patterns, we need to have some way to take a snapshot of where we are in the evaluation of a complex piece of code, so that we might later resume execution at that point. In the coroutine example, the two threads need to have a snapshot of where they were in the enumeration of their tree's leaves. In the abort example, we need to have a snapshot of where to pick up again if some embedded piece of code aborts. Sometimes we might distill that snapshot into a data structure like a zipper. But we might not always know how to do so; and learning how to think about these snapshots without the help of zippers will help us see patterns and similarities we might otherwise miss.
+In both of these patterns --- coroutines and exceptions/aborts --- we need to have some way to take a snapshot of where we are in the evaluation of a complex piece of code, so that we might later resume execution at that point. In the coroutine example, the two threads need to have a snapshot of where they were in the enumeration of their tree's leaves. In the abort example, we need to have a snapshot of where to pick up again if some embedded piece of code aborts. Sometimes we might distill that snapshot into a data structure like a zipper. But we might not always know how to do so; and learning how to think about these snapshots without the help of zippers will help us see patterns and similarities we might otherwise miss.
A more general way to think about these snapshots is to think of the code we're taking a snapshot of as a *function.* For example, in this code:
and we can think of the code starting with `let foo_result = ...` as a function, with the box being its parameter, like this:
+ let foo_result = < >
+ in foo_result + 100
+
+or, spelling out the gap `< >` as a bound variable:
+
fun box ->
let foo_result = box
in (foo_result) + 1000
The key idea behind working with continuations is that we're *inverting control*. In the fragment above, the code `(if x = 1 then ... else snapshot 20) + 100`---which is written as if it were to supply a value to the outside context that we snapshotted---itself *makes non-trivial use of* that snapshot. So it has to be able to refer to that snapshot; the snapshot has to somehow be available to our inside-the-box code as an *argument* or bound variable. That is: the code that is *written* like it's supplying an argument to the outside context is instead *getting that context as its own argument*. He who is written as value-supplying slave is instead become the outer context's master.
-In fact you've already seen this several times this semester---recall how in our implementation of pairs in the untyped lambda-calculus, the handler who wanted to use the pair's components had *in the first place to be supplied to the pair as an argument*. So the exotica from the end of the seminar was already on the scene in some of our earliest steps. Recall also what we did with v2 and v5 lists. Version 5 lists were the ones that let us abort a fold early:
-go back and re-read the material on "Aborting a Search Through a List" in [[Week4]].
+In fact you've already seen this several times this semester---recall how in our implementation of pairs in the untyped lambda-calculus, the handler who wanted to use the pair's components had *in the first place to be supplied to the pair as an argument*. So the exotica from the end of the seminar was already on the scene in some of our earliest steps. Recall also what we did with our [[abortable list traversals|/topics/week12_abortable_traversals]].
This inversion of control should also remind you of Montague's treatment of determiner phrases in ["The Proper Treatment of Quantification in Ordinary English"](http://www.blackwellpublishing.com/content/BPL_Images/Content_store/Sample_chapter/0631215417%5CPortner.pdf) (PTQ).