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How OCaml type checker works -- or what polymorphism and garbage collection have in common


There is more to Hindley-Milner type inference than the Algorithm W. In 1988, Didier Rémy was looking to speed up the type inference in Caml and discovered an elegant method of type generalization. Not only it is fast, avoiding the scan of the type environment. It smoothly extends to catching of locally-declared types about to escape, to type-checking of universals and existentials, and to implementing MLF.

Alas, both the algorithm and its implementation in the OCaml type checker are little known and little documented. This page is to explain and popularize Rémy's algorithm, and to decipher a part of the OCaml type checker. The page also aims to preserve the history of Rémy's algorithm.

The attraction of the algorithm is its insight into type generalization as dependency tracking -- the same sort of tracking used in automated memory management such as regions and generational garbage collection. Generalization can be viewed as finding dominators in the type-annotated abstract syntax tree with edges for shared types. Fluet and Morrisett's type system for regions and MetaOCaml environment classifiers use the generalization of a type variable as a criterion of region containment. Uncannily, Rémy's algorithm views the region containment as a test if a type variable is generalizable.

Inside OCaml type checker



This page started as notes taken to understand the OCaml type checking code, which is extensive, complex and hardly documented. Digging through the code unearthed real gems. One of them, an efficient and elegant method of type generalization, is spotlight here.

OCaml generalization is based on tracking of so-called levels of a type. The very same levels also ensure that types defined within a module do not escape into a wider scope. Levels hence enforce the region discipline for locally introduced type constructors. It is intriguing how generalization and regions are handled so uniformly. There are even more applications of levels in the OCaml type checker, for records with polymorphic fields and existentials. MetaOCaml indirectly relies on levels to track the scope of future-stage bindings. There is a common refrain in all these applications: tracking dependencies, computing region containment or dominators in data-dependency graphs. One is immediately reminded of the region-based memory management by Tofte and Talpin. As Fluet and Morrisett showed, Tofte and Talpin type system for regions can be encoded in System F, relying on universal quantification to statically prevent allocated data from escaping their region. Dually, the level-based generalization relies on detecting escapes of a type variable to determine its region and hence the place for its universal quantification.

OCaml's generalization is a (partial) implementation of the algorithm discovered by Didier Rémy back in 1988. The idea is to explicitly represent the sharing of types in the type-annotated abstract syntax tree. A type variable can only be quantified at a node that dominates all occurrences of that variable. Generalization amounts to the incremental computation of graph dominators. Rémy's MLF is the natural outgrowth of this idea.

Unfortunately, Rémy's generalization algorithm and the underlying ideas are little known. The implementations, such as the one in OCaml, do not seem to be documented at all, aside from a couple of brief puzzling comments in the OCaml source code. They ought to be widely known. Towards this goal, the present page sets to (i) motivate and explain the algorithm, expose its intuitions and sketch implementations; (ii) help decipher OCaml type checker.

The second part of this page aims to be a commentary on a portion of the OCaml type-checker, and is, therefore, quite technical. It refers to OCaml 4.00.1 type checking code, located in the directory typing/ of the OCaml distribution. The file is the core type checker: it annotates nodes of the abstract syntax tree with types and the typing environment. To be precise, it transforms Parsetree (defined in parsing/parsetree.mli) into Typedtree. The file implements unification and level manipulation functions.

I am indebted to Didier Rémy for his comments, explanations, intuitions and recollections of the discovery of the algorithm. I thank Jacques Garrigue for helpful comments and explanations of more applications of levels within the OCaml type checker. Additional references provided by Matthew Fluet and Baris Aktemur are gratefully acknowledged.

The current version is February 2013.
Didier Rémy: Extension of ML Type System with a Sorted Equational Theory on Types
Research Report 1766, Institut National de Recherche en Informatique et Automatique, Rocquencourt, BP 105, 78 153 Le Chesnay Cedex, France, 1992.
< >

Matthew Fluet and J. Gregory Morrisett: Monadic Regions
J. Functional Programming, 2006, v16, N4-5, pp. 485-545.
The paper shows that parametric polymorphism is all that needed for a sound type system of memory regions.



This background section reminds the type generalization in the Hindley-Milner type system, stressing subtle points and inefficiencies of the naive implementation. These inefficiencies motivated Rémy's discovery of the level-based generalization algorithm.

Recall that generalization GEN(G,t) of the type t with respect to the type environment G is quantifying free type variables of t that do not occur as free in G. In Greek: GEN(G,t) = ∀ α1 ... αn. t where {α1 ... αn} = FV(t) - FV(G). A Hindley-Milner system applies the generalization, to convert a type to a type schema, when type checking let:

     G |- e : t    G, (x:GEN(G,t)) |- e2 : t2
     G |- let x = e in e2 : t2

That is, when inferring the type for let x = e in e2, a free type variable in the type of e is quantified if the type variable does not occur in the type environment. ML adds another condition for generalization, so-called value restriction: the type of e is generalized only if e, by the look of it, has no visible side-effect -- technically, e passes the syntactic test of being nonexpansive. OCaml relaxes the value restriction, see later on this page.

Here is a trivial example of generalization:

     fun x -> let y = fun z -> z in y
     (* 'a -> ('b -> 'b) *)
The type checker infers for fun z ->z the type β->β with the fresh, and hence unique, type variable β. The expression fun z ->z is syntactically a value, generalization proceeds, and y gets the type ∀β.β->β. Because of the polymorphic type, y may occur in differently typed contexts -- may be applied to arguments of different types, -- as in
     fun x -> 
       let y = fun z -> z in
       (y 1, y true)
     (* 'a -> int * bool *)

Generalization Gen(G,t) quantifies over only those free type variables of t that do not occur in G. This condition is subtle but crucial: without it, the unsound type α->β is inferred for the function

     fun x -> let y = x in y

To elaborate: to infer the type of a function, we infer the type of its body in the environment in which x:α where α is a fresh type variable. The form let y=x in ... adds to the environment y: Gen(x:α,α). Clearly α does occur in the environment x:α. If we quantify over it nevertheless, y receives the polymorphic type ∀α.α, which can then be instantiated to any type. The result is the function that ostensibly converts its argument to the value of any type whatsoever.

Therefore, for the soundness of the type system, we must make sure that the type variable to quantify does not occur in the type environment. Naively, we could scan the type environment, looking through the type of each binding -- in fact, the original Caml did exactly that. The type environment however can be very large. Typically ML functions contain long sequences of lets. A non-recursive let has in its type environment the bindings of all previous lets; the environment of a recursive let has the bindings of all let siblings. Searching the environment as part of the generalization for a single let takes time linear in the function size; the type checking of the whole program will be quadratic then. (Except for pathological cases, Hindley-Milner type inference scales nearly linearly with the program size.) The inefficient generalization was one of the main reasons for the slow speed of Caml compilation, Didier Rémy recalls. Bootstrapping the compiler and type checking two mutually recursive functions for compiling patterns and expressions took 20 minutes.

There has to be a way to avoid scanning the environment. The next section gives the idea.


Unsound generalization as memory mismanagement

This section begins to introduce the ideas behind Rémy's algorithm, relating them to region-based memory management. For concreteness we will be using a toy Hindley-Milner type inferencer. In this section, the inferencer has the unsound generalization function that quantifies free type variables in a type with no regard for the environment. We type check in detail three trivial examples, and relate the inferring of unsound types with the common problems of the manual memory management, releasing memory still in use. The unsound generalization will be fixed in the next section, drawing the inspiration from the standard methods of preventing premature deallocation of resources.

Although our Hindley-Milner type inferencer is toy, it shares many implementation decisions (and even some function names) with the real OCaml type checker. Understanding it will help when we turn to OCaml internals later on this page.

Our toy language is the standard pure lambda-calculus with let. Its expressions are

     type exp = 
       | Var of varname                      (* variable                *)
       | App of exp * exp                    (* application: e1 e2      *)
       | Lam of varname * exp                (* abstraction: fun x -> e *)
       | Let of varname * exp * exp          (* let x = e in e2         *)
Types are comprised of type variables, quantified type variables and function types:
     type qname = string
     type typ = 
       | TVar of tv ref               (* type (schematic) variable *)
       | QVar of qname                (* quantified type variable *)
       | TArrow of typ * typ
     and tv = Unbound of string | Link of typ
Type schemas in the Hindley-Milner system are in the prenex form (that is, universal quantifiers are all outside), and so the quantifiers need not be represented explicitly. Types with QVar are type schemas; without -- simple types.

In the Prolog tradition, type variables are represented as reference cells. An unbound variable contains the null or the self pointer -- or, in our case, the name of the variable for easy printing. When a free type variable is unified with some type t', the reference cell is overwritten with the pointer to t'. To prevent cyclical (and, for us, unsound) types, the `occurs check' is performed first: occurs tv t' traverses t' raising an exception if it comes across the type variable tv:

     let rec unify : typ -> typ -> unit = fun t1 t2 ->
       if t1 == t2 then ()                   (* t1 and t2 are physically the same *)
       else match (t1,t2) with
       | (TVar ({contents = Unbound _} as tv),t') | (t',TVar ({contents = Unbound _} as tv)) -> 
           occurs tv t'; tv := Link t'
       | (TVar {contents = Link t1},t2) | (t1,TVar {contents = Link t2}) -> 
           unify t1 t2
       | (TArrow (tyl1,tyl2), TArrow (tyr1,tyr2)) ->
           unify tyl1 tyr1;
           unify tyl2 tyr2
       (* everything else is error *)

The type checker is totally standard. It infers the type for the expression exp in the type environment env:

     type env = (varname * typ) list
     let rec typeof : env -> exp -> typ = fun env -> function
       | Var x     -> inst (List.assoc x env)
       | Lam (x,e) -> 
           let ty_x = newvar () in
           let ty_e = typeof ((x,ty_x)::env) e in
       | App (e1,e2) ->
           let ty_fun = typeof env e1 in
           let ty_arg = typeof env e2 in
           let ty_res = newvar () in
           unify ty_fun (TArrow (ty_arg,ty_res));
       | Let (x,e,e2) -> 
           let ty_e = typeof env e in
           typeof ((x,gen ty_e)::env) e2
The function newvar allocates a new TVar, with a unique name. The function inst instantiates a type schema, that is, replaces each QVar with a fresh TVar. It is also standard. The generalization function is unsound: it quantifies all free variables in the type regardless of the environment:
     let rec gen : typ -> typ = function      (* unsound! *)
       | TVar {contents = Unbound name} -> QVar name
       | TVar {contents = Link ty}      -> gen ty
       | TArrow (ty1,ty2)               -> TArrow (gen ty1, gen ty2)
       | ty -> ty
The quantification replaces a TVar with the corresponding QVar. The original TVar is hence implicitly deallocated: When a free variable is bound, it `disappears', being replaced by the `pointer' to the binder.

With respect to type variables, typeof allocates free variables, unifies them, and deallocates, after quantification. Let us type check simple examples observing the sequence of these three main operations that affect free type variables. The first example is the one where nothing should go wrong:

     fun x -> let y = fun z -> z in y
The trace of type-checking, showing only type-variable related operations, is as follows.
     1    ty_x = newvar ()          (* fun x -> ...               *)
     2      ty_e =                  (* let y = fun z -> z in y    *)
     3         ty_z = newvar ();    (* fun z -> ...               *)
     3         TArrow(ty_z,ty_z)    (* inferred for: fun z -> z   *)
     2      ty_y = gen ty_e         (* ty_z remains free, and so  *)
     2      deallocate ty_z         (* quantified and disposed of *)
     1    TArrow(ty_x, inst ty_y)   (* inferred for: fun x -> ... *)
The number in the first column is the depth for the recursive invocations of typeof. Since typeof recurs on each non-leaf node of the abstract syntax tree (AST), this recursive invocation depth is the depth in the AST of the node being type checked. The inferred type is 'a -> 'b -> 'b, as expected. Nothing went wrong.

The second example is the one we saw before, for which the unsound generalization gives the unsound type 'a->'b:

     fun x -> let y = x in y
Diagramming the TVar operations as before reveals the problem:
     1    ty_x = newvar ()          (* fun x -> ...                 *)
     2      ty_e =                  (* let y = x in y               *)
     3         inst ty_x            (* inferred for x, same as ty_x *)
     2      ty_y = gen ty_e         (* ty_x remains free, and is    *)
     2      deallocate ty_x         (* quantified, and disposed of  *) 
     1    TArrow(ty_x, inst ty_y)   (* inferred for: fun x -> ...   *)
The type variable ty_x is part of the return type, used at depth 1 -- and yet it is quantified and disposed of at depth 2. We disposed of the value still in use.

The third example is also problematic. The unsound generalization again gives the unsound type ('a->'b) -> ('c ->'d):

     fun x -> let y = fun z -> x z in y
The diagram shows a memory management problem again:
     1    ty_x = newvar ()          (* fun x -> ...               *)
     2      ty_e =                  (* let y = ...                *)
     3         ty_z = newvar ()     (* fun z -> ...               *)
     4           ty_res = newvar () (* typechecking: x z          *)
     4           ty_x :=            (* as the result of unify     *)
     4              TArrow (ty_z,ty_res)
     4           ty_res             (* inferred for: x z          *)
     3         TArrow(ty_z,ty_res)  (* inferred for: fun z -> x z *)
     2      ty_y = gen ty_e         (* ty_z, ty_res remain free   *)
     2      deallocate ty_z         (* quantified and disposed of *)
     2      deallocate ty_res       (* quantified and disposed of *)
     1    TArrow(ty_x, inst ty_y)   (* inferred for: fun x -> ... *)
The type variables ty_z and ty_res are quantified over and hence disposed of at depth 2, and yet they are part of TArrow (ty_z,ty_res) that is assigned to ty_x, which, in turn, is part of the result.

All unsound examples had a `memory management problem', deallocating memory (TVar) still being used. This is no accident. When a type variable is quantified over, later on it can be instantiated with any type whatsoever, with no limitations and in any context. However, if a type variable also appears in the type environment G, no longer can we replace the type variable with any type without affecting the rest of the type checking. Likewise, when we free a piece of memory, we give the run-time the permission to reallocate it and overwrite with arbitrary data. The rest of our program should not depend on what happens later with the deallocated memory -- provided it was really free, not needed further in the program. In fact, one may define `memory not in use' as arbitrary non-deterministic changes to that memory not affecting the rest of the program. Deallocating memory still in use will affect the rest of the program -- often, crash it. Incidentally, unsound types inferred for our examples often lead to the same result.

References [9K]
Complete code for the toy type inferencer with the unsound generalization, with many more examples of unsound inference


Efficient generalization with levels

This section continues the exposition of the ideas behind Rémy's algorithm. Now that we have seen how the unsound generalization relates to the releasing of memory still in use, we apply the standard fix for premature deallocation -- ownership tracking, or regions -- and cure the unsound generalization without much overhead. We develop two algorithms. The simpler one, sound_eager, is motivated and explained in this section. The optimal sound_lazy, which captures the main features of the Rémy algorithm, is presented next.

Clearly, before deallocating memory we must check if it is still in use. Naively, we could scan all memory known to be in use looking for references to the deallocation candidate -- in other words, do the full garbage-collection marking pass and see if our piece of memory got marked. Put it this way, the check seems awfully expensive. At least we should wait until garbage accumulates, to collect it en masse. Alas, in the Hindley-Milner type system we cannot delay quantification arbitrarily, since the generalized type can be used right away.

More promising is ownership tracking, associating an allocated resource with an owner, an object or a function activation. Only the owner may deallocate its resources. A similar strategy is regions, which are areas of memory for heap-allocated data created by a lexically-scoped letregion primitive. When letregion goes out of scope, its whole whole region is summarily deallocated. This idea matches the generalization well. In the Hindley-Milner system, generalization is always a part of let. A let-expression let x = e in e2 is the natural owner of all type variables allocated when inferring the type of e. When the type of e is found, all free type variables still owned by the let-expression can be disposed of, that is, quantified.

These intuitions underlie the sound and efficient generalization algorithms. The first is sound_eager, described in the rest of the section. Its code differs only in small, but significant, details from the toy Hindley-Milner inferencer from the previous section. We will only explain these small differences; the complete code is available below. The main difference is that free type variables, albeit unbound, are now owned, and contain the `pointer' to their owner. The owner, always a let expression, is identified by a positive integer called level. This level is essentially the de Bruijn level, only referring to the owner rather than the binder. That is, the level is the nesting depth of the owning let expression in the abstract syntax tree (AST); level 1 corresponds to the (implicit) top-level let. (Incidentally, although both lets in (let x = e1 in eb1, let y = e2 in eb2) have level 2, no confusion can arise as neither let is in each other scope and hence their regions are disjoint.) Since the depth of typeof recursion equals the AST depth of the expression it type checks, the level is equal to the let-expression's type checking recursion depth. That depth is simple to determine, with the help of one reference cell.

     type level = int
     let current_level = ref 1
     let enter_level () = incr current_level
     let leave_level () = decr current_level
The type inferencer maintains the let type-checking depth:
     let rec typeof : env -> exp -> typ = fun env -> function
       ... (* the other cases are the same as before *)
       | Let (x,e,e2) -> 
           enter_level ();
           let ty_e = typeof env e in
           leave_level ();
           typeof ((x,gen ty_e)::env) e2
The only change to the main type-inference function was adding enter_level and leave_level to track the level. The rest of typeof is literally the same as in the original toy version.

Free type variables now carry the level identifying their owner. A freshly allocated type variable receives the current_level, meaning that its owner is the latest let being type-checked. (In region-based memory management, all new memory is allocated in the innermost alive region.)

     type typ = 
       | TVar of tv ref               (* type (schematic) variable *)
       | QVar of qname                (* quantified type variable *)
       | TArrow of typ * typ
     and tv = Unbound of string * level | Link of typ
     let newvar : unit -> typ =
      fun () -> TVar (ref (Unbound (gensym (),!current_level)))

Just as an assignment may change the owner of an allocated memory, unification may change the level of a free type variable. For example, if ty_x and ty_y are both free, ty_y has level 2, ty_x has level 1, and ty_x is unified with the type TArrow(ty_y,ty_y), the arrow type and its components are exported into region 1, and so the level of ty_y is changed to 1. One may view the above unification as replacing all occurrences of ty_x with TArrow(ty_y,ty_y). Some occurrences may be outside the scope of the inner, level-2 let. Therefore, when the type checking of that inner let finishes, ty_y should not be deallocated. With the updated ty_y level, it won't be. Thus unifying a free type variable ty_x with t has to update the levels of each free type variable ty_y in t to the smallest of ty_y and ty_x levels. Unifying a free type variable with t also has to do the occurs check, which too traverses the type. The two traversals can be merged. The new occurs does the occurs check and updates the levels:

     let rec occurs : tv ref -> typ -> unit = fun tvr -> function
       | TVar tvr' when tvr == tvr' -> failwith "occurs check"
       | TVar ({contents = Unbound (name,l')} as tv) ->
           let min_level = 
             (match !tvr with Unbound (_,l) -> min l l' | _ -> l') in
           tv := Unbound (name,min_level)
       | TVar {contents = Link ty} -> occurs tvr ty
       | TArrow (t1,t2)            -> occurs tvr t1; occurs tvr t2
       | _ -> ()

The only difference from the original occurs code is the second clause in the pattern-match. The unification code does not have to be modified at all. Finally, we fix the generalization function, to make it sound:

     let rec gen : typ -> typ = function
       | TVar {contents = Unbound (name,l)} 
           when l > !current_level -> QVar name
       | TVar {contents = Link ty} -> gen ty
       | TArrow (ty1,ty2) -> TArrow (gen ty1, gen ty2)
       | ty -> ty

The change is minimal: the condition when l > !current_level. Recall the new typeof code:

     let rec typeof : env -> exp -> typ = fun env -> function
       ... (* the other cases are the same as before *)
       | Let (x,e,e2) -> 
           enter_level ();
           let ty_e = typeof env e in
           leave_level ();
           typeof ((x,gen ty_e)::env) e2
It invokes gen after the region established for type checking e exits. A free type variable still owned by that region will have the level greater than the current. Since the region is now dead, any such type variable may be deallocated, that is, quantified.

These are all the changes of sound_eager from the unsound toy algorithm, which fix the type inference. Here is the old problematic example

     fun x -> let y = x in y
Diagramming the TVar operations shows no problems now:
     1  1   ty_x/1 = newvar ()          (* fun x -> ...                 *)
     2  2     ty_e =                    (* let y = x in y               *)
     3  2        inst ty_x/1            (* inferred for x, same as ty_x *)
     2  1     ty_y = gen ty_e           (* ty_x/1 remains free, but is  *)
                                        (* level = current, can't       *) 
                                        (* quantify, can't dispose      *)
     1  1   TArrow(ty_x/1, inst ty_y)   (* inferred for: fun x -> ...   *)
The first column of numbers shows the typeof recursion depth, or the depth of the AST node being type-checked. The number in the second column is the current_level, the let nesting depth. We write the level of a free type variable after the slash, as in ty_x/1. That variable is no longer quantified by gen at depth 2 (level 1) since ty_x/1 belongs to to the current, still active region 1. Therefore, the inferred type is 'a->'a, as expected.

In a slightly more complex example,

     fun x -> let y = fun z -> x in y
the type variable ty_x for the type of x is allocated at level 1, whereas ty_z is allocated at level 2. After the inner let, region 2, is finished, ty_z/2 will be quantified and disposed of, but ty_x/1 will not. The inferred type therefore is 'a->'b->'a. The reader is encouraged to diagram other examples, to check that the inferred types are sound.

Level tracking may look like reference counting. However, rather than counting the number of users for a free type variable, we keep track of only one user, the one with the widest scope. Level tracking does look a lot like generational garbage collection: Memory is allocated in the young generation, and summarily disposed of at the minor (youngest) collection, unless it is `re-parented' or referenced from the stack. The old generation does not have to be scanned for references to the new generation, since no such references are expected -- unless there was an assignment of a young value to the field of an old data structure. A generational garbage collector (such OCaml GC) keeps track of inter-generational assignments. At the minor collection, young data referred from the old are promoted to the old generation. Type generalization indeed looks very similar to the minor GC collection.

References [10K]
Complete code for the toy type inferencer with the sound_eager generalization, with many more examples of now sound inference


Even more efficient level-based generalization

This section continues the exposition of the ideas behind Rémy's algorithm and presents sound_lazy, an optimized version of sound_eager from the previous section. The sound_lazy algorithm eschews repeated, unnecessary traversals of the type during unification, generalization and instantiation, and avoids copying the parts that do not contain variables to generalize or instantiate, thus improving sharing. The algorithm delays the occurs check and the level updates, so that the unification with a free type variable takes constant time. Levels are updated incrementally and on demand. All in all, sound_lazy embodies the main ideas of Rémy's algorithm. Some of these ideas are implemented in the OCaml type checker.

To carry on the optimizations, we change the syntax of types. Recall that in sound_eager, types were comprised of free or bound type variables TVar, (implicitly universally) quantified type variables QVar and function types TArrow. The first, seemingly unprincipled change, is to eliminate QVar as a distinct alternative and dedicate a very large positive integer -- which should be treated as the inaccessible ordinal ω -- as a generic_level. A free type variable TVar at generic_level is taken to be a quantified type variable. More substantially, all types, not only free type variables, have levels now. The level of a composite type (TArrow in our case) is an upper, not necessarily exact, bound on the levels of its components. In other words, if a type belongs to an alive region, all its components should be alive. It immediately follows that if a (composite) type is at generic_level, it may contain quantified type variables. Contrapositively, if a type is not at generic_level, it does not contain any quantified variable. Therefore, instantiating such a type should return the type as it is without traversing it. Likewise, if the level of a type is greater than the current level, it may contain free type variables to generalize. On the other hand, the generalization function should not even bother traversing a type whose level is equal or less than the current. This is the first example of how levels help eliminate traversals and rebuildings of a type, improving sharing.

Unifying a type t with a free type variable should update t's level to the level of the type variable if the latter level is smaller. For a composite type, such an update means recursively updating the levels of all components of the type. To postpone costly traversals, we give composite types two levels: level_old is an upper bound on the levels of type's components; level_new, which is less or equal to level_old, is the level the type should have after the update. If level_new < level_old, the type has pending level updates. The syntax of types in sound_eager is thus

     type level = int
     let generic_level = 100000000           (* as in OCaml typing/ *)
     let marked_level  = -1                  (* for marking a node, to check*)
                                             (* for cycles                  *)
     type typ = 
       | TVar of tv ref
       | TArrow of typ * typ * levels
     and tv = Unbound of string * level | Link of typ
     and levels = {mutable level_old : level; mutable level_new : level}

We have not explained marked_level. The occurs check on each unification with a free type variable is expensive, raising the algorithmic complexity of the unification and type checking. We now postpone this check, until the whole expression is type checked. In the meanwhile, unification may create cycles in types. Type traversals have to check for cycles, or risk divergence. The marked_level is assigned temporarily to level_new of a composite type to indicate the type is being traversed. Encountering marked_level during a traversal means detecting a cycle, which raises the occurs check error. Incidentally, in OCaml types are generally cyclic: (equi-)recursive types arise when type checking objects and polymorphic variants, and when the -rectypes compiler option is set. The OCaml type checker uses a similar marked-level trick to detect cycles and avoid divergence.

The sound_lazy unification has several important differences from sound_eager:

     let rec unify : typ -> typ -> unit = fun t1 t2 ->
       if t1 == t2 then ()                   (* t1 and t2 are physically the same *)
       else match (repr t1,repr t2) with
       | (TVar ({contents = Unbound (_,l1)} as tv1) as t1,      (* unify two free vars *)
         (TVar ({contents = Unbound (_,l2)} as tv2) as t2)) ->
            if l1 > l2 then tv1 := Link t2 else tv2 := Link t1  (* bind the higher-level var *)
       | (TVar ({contents = Unbound (_,l)} as tv),t')
       | (t',TVar ({contents = Unbound (_,l)} as tv)) -> 
           update_level l t';
           tv := Link t'
       | (TArrow (tyl1,tyl2,ll), TArrow (tyr1,tyr2,lr)) ->
           if ll.level_new = marked_level || lr.level_new = marked_level then
             failwith "cycle: occurs check";
           let min_level = min ll.level_new lr.level_new in
           ll.level_new <- marked_level; lr.level_new <- marked_level;
           unify_lev min_level tyl1 tyr1;
           unify_lev min_level tyl2 tyr2;
           ll.level_new <- min_level; lr.level_new <- min_level
       (* everything else is the unification error *)
     and unify_lev l ty1 ty2 =
       let ty1 = repr ty1 in
       update_level l ty1;
       unify ty1 ty2
where the auxiliary repr, like OCaml's Btype.repr, chases links of bound variables returning a free variable or a constructed type. Unlike OCaml, we do path compression. The unification function no longer does the occurs check; therefore, it has to make an effort to detect accidentally created cycles. Unifying with a free variable now takes constant time, to bind the variable after a shallow update_level.

The function update_level is one of the key parts of the optimized algorithm. Often, it merely promises to update the level of a type to the given level. It works in constant time and maintains the invariant that a type level may only decrease. The level of a type variable is updated immediately. For a composite type, level_new is set to the desired new level if the latter is smaller. In addition, if previously level_new and level_old were the same, the type is put into the to_be_level_adjusted queue for later update of the levels of the components. This work queue is akin to the list of assignments from the old generation to the young maintained by a generational garbage collector (such as the one in OCaml). Incidentally, a unification of two TArrow types has to traverse the types anyway, and so it does pending level updates along the way.

     let to_be_level_adjusted = ref []
     let update_level : level -> typ -> unit = fun l -> function
       | TVar ({contents = Unbound (n,l')} as tvr) -> 
           assert (not (l' = generic_level));
           if l < l' then
             tvr := Unbound (n,l)
       | TArrow (_,_,ls) as ty -> 
           assert (not (ls.level_new = generic_level));
           if ls.level_new = marked_level then failwith "occurs check";
           if l < ls.level_new then begin
             if ls.level_new = ls.level_old then
               to_be_level_adjusted := ty :: !to_be_level_adjusted;
             ls.level_new <- l
       | _ -> assert false

Pending level updates must be performed before generalization: After all, a pending update may decrease the level of a type variable, promoting it to a wider region, and hence save the variable from quantification. Not all pending updates have to be forced however -- only of those types whose level_old > current_level. Otherwise, a type contains no variables generalizable at the present point, and the level update may be delayed further.

The generalization function searches for free TVars that belong to a dead region (that is, whose level is greater than the current) and sets their level to generic_level, hence quantifying the variables. The function traverses only those parts of the type that may contain type variables to generalize. If a type has the (new) level of current_level or smaller, all its components belong to live regions and hence the type has nothing to generalize. After the generalization, a composite type receives generic_level if it contains a quantified type variable. Later on, the instantiation function will, therefore, only look through those parts of the type whose level is generic_level.

     let gen : typ -> unit = fun ty ->
       force_delayed_adjustments ();
       let rec loop ty =
         match repr ty with
         | TVar ({contents = Unbound (name,l)} as tvr)
           when l > !current_level -> tvr := Unbound (name,generic_level)
         | TArrow (ty1,ty2,ls) when ls.level_new > !current_level ->
           let ty1 = repr ty1 and ty2 = repr ty2 in
           loop ty1; loop ty2;
           let l = max (get_level ty1) (get_level ty2) in
           ls.level_old <- l; ls.level_new <- l   (* set the exact level upper bound *)
         | _ -> ()
       in loop ty

The type checker typeof remains the same, entering a new region when type checking a let expression. Please see the source code for details.

We have presented the optimized sound_lazy type generalization algorithm that not only avoids scanning the whole type environment on each generalization. The algorithm also avoids the occurs check on each unification with a free type variable, so that this unification takes constant time. The algorithm eliminates unnecessary type traversals and copying, saving time and memory. Two ideas underlie the optimizations, besides the type levels for free type variables. First is the assigning of levels to composite types, to give us an idea what a type may contain without looking though it. The second principle is delaying expensive actions (type traversals) with the hope they will get done in the future alongside of something else. In other words, if dealing with a problem is postponed long enough, it may go away: procrastination sometimes helps.

References [18K]
Complete code for the optimized toy type inferencer, again with many examples


Generalization with levels in OCaml

This OCaml internals section describes the implementation of the type levels in the OCaml type checker and their application for efficient generalization. The next section shows how the levels help prevent escapes of local types and type check existentials.

The ideas behind the type generalization in OCaml have been presented in the previous sections, in the form of the toy algorithms sound_eager and sound_lazy. Their code has been intentionally written to resemble the OCaml type checker, often using the same function names. The OCaml type checker implements the sound_eager algorithm with a few optimizations from sound_lazy. OCaml is far more complicated: whereas unification in the toy code takes just a few lines, the OCaml unification code, in, takes 1634 lines. Nevertheless, understanding the toy algorithms should help in deciphering the OCaml type checker.

Like the sound_eager algorithm, the OCaml type checker does the occurs check and the levels update on each unification with a free variable; one can clearly see that from the code of Ctype.unify_var. On the other hand, like in sound_lazy, the OCaml type checker assigns levels to all types, not only to type variables -- see type_expr in types.mli. One reason is to detect escaping local type constructors (described in the next section). Also like in sound_lazy, generic_level distinguishes quantified type variables and the types that may contain quantified variables (so-called `generic types'). Therefore, the schema instantiation function (Ctype.instance and Ctype.copy) won't traverse and copy non-generic parts of a type, returning them as they are, which improves sharing. Type variables at generic_level are printed like 'a; with other levels, as '_a. As in our toy algorithms, a mutable global Ctype.current_level tracks the current level, which is assigned to newly created types or type variables (see Ctype.newty and Ctype.newvar). The current_level is increased by enter_def() and decreased by end_def(). Besides the current_level, there is also nongen_level, used when type checking a class definition, and global_level used for type variables in type declarations.

A very simplified code for type-checking let x = e in body is as follows.

     let e_typed =
       enter_def ();
       let r = type_check env e_source in
       end_def (); 
     generalize e_typed.exp_type;
     let new_env = bind env x e_typed.exp_type in
     type_check new_env body_source
Here, e_source is the abstract syntax tree, or Parsetree.expression for the expression e and e_typed is the Typedtree.expression, the abstract syntax tree in which each node is annotated with its inferred type, the field exp_type.

Thus the overall type generalization pattern, often seen in the OCaml type checker, is

     let ty =
         enter_def ();
         let r = ... let tv = newvar() in ... (... tv ...)
         end_def ();
         r in
     generalize ty

If tv was not unified with something that existed in the environment before enter_def(), the variable will be generalized. The code looks quite like our toy code.

Interestingly, levels have another use, enforcing the region discipline for local type declarations.


Type Regions

The OCaml type checker relies on type levels also to check that types are not used before being declared and that locally introduced types do not escape into a wider scope. Unification, akin to assignment, facilitates both mischiefs. We have seen how type levels are related to region-based memory management. It is not surprising then that the levels help rein in the unification, preventing resource mismanagement -- this time, not with type variables but with type constants.

OCaml, unlike SML, supports local modules, or modules defined in local scope, via the let module form. A local module may declare a type, and may even let this type escape, as in

     let module M = struct type t = Foo let x = Foo end in M.x;;
     Error: This `let module' expression has type M.t
     In this type, the locally bound module name M escapes its scope
Such an escape must be flagged as an error. Otherwise, the expression will receive the type M.t where M and M.t come into scope only inside the expression. This problem is akin to returning the address of an automatic local variable from a C function:
     char * esc_res(void)
       char str [] = "local string";
       return str;
A locally declared type can escape not only through the result type but also by unification with an existing type variable:
     fun y -> let module M = struct type t = Foo let r = y Foo end in ();;
     Error: This expression has type t but an expression was expected of type 'a
          The type constructor t would escape its scope
This sort of error is also familiar to C programmers:
     char * y = (char*)0;
     void esc_ext(void)
       char str [] = "local string";
       y = str;

Even with ordinary, top-level rather than local, modules may have type escaping problems. Here is the example taken from a comment in OCaml type checker:

     let x = ref []
     module M = struct type t let _ = (x : t list ref) end
The module M defines a local type t. The variable x has the non-generic type '_a list ref. The type attribution causes x, defined prior to t, to have the type x : t list ref. OCaml cannot let such escapes go uncaught. Under no circumstances the scope of a type constructor may wider that the scope of its declaration. Type levels enforce this region-like discipline for type constructors.

The OCaml type checker already supports regions for the sake of type generalization, providing tools for entering a new region and destroying it (begin_def and end_def), associating types to their owner region, and tracking ownership changes during unification. What remains is to associate a type constructor to the region created at the point of its declaration. A type constructor can escape if used in a type whose region is wider than the type constructor's region -- in other words, if a type may outlive its type constructors. Affirmatively, we aim to enforce the property that the region of a type constructor declaration be wider than the region of any type with that type constructor: the declaration of a type constructor must dominate all its uses.

Type regions are identified by a positive number, type level, which is just the nesting depth of the region. Each type has the field level with the level of its owner region. Luckily, there is an unexpected way to attribute the type level also to a type constructor. Type constructors, data constructors, term variables may be re-defined within an OCaml program: a type can be re-declared, a variable can be rebound several times. OCaml relies on identifiers (see to distinguish among differently declared or bound occurrences of the same name. An identifier has the name and the timestamp, a positive number. The global mutable Ident.currentstamp keeps the `current time' and advances it when a new identifier is created, by a declaration or a binding. The timestamp of the identifier is thus its binding time. The binding time is the natural way to relate an identifier to a type region. If the current time is set to the current level, new identifiers will have their binding time not smaller than the current level: they will be regarded as owned by the current type region. In type-level terms, the non-escaping property states that the level of a type is no less than the binding time of each type constructor within the type.

Unification, specifically, unification with a free type variable -- akin to assignment -- may change the ownership of a type, and so has to update the type level accordingly. The very same Ctype.update_level function can hence check that the non-escaping property still holds.

We can now understand the OCaml code for type checking a local module, the expression let module name = modl in body, excerpted below from

     | Pexp_letmodule(name, smodl, sbody) ->
         let ty = newvar() in
         (* remember original level *)
         begin_def ();
         Ident.set_current_time ty.level;
         let context = Typetexp.narrow () in
         let modl = !type_module env smodl in
         let (id, new_env) = Env.enter_module name.txt modl.mod_type env in
         Typetexp.widen context;
         let body = type_expect new_env sbody ty_expected in
         (* go back to original level *)
         end_def ();
         (* Check that the local types declared in modl don't escape
            through the return type of body
         begin try
           Ctype.unify_var new_env ty body.exp_type
         with Unify _ ->
           raise(Error(loc, Scoping_let_module(name.txt, body.exp_type)))
         re {
           exp_desc = Texp_letmodule(id, name, modl, body);
           exp_loc = loc; exp_extra = [];
           exp_type = ty;
           exp_env = env }

The type variable ty is created to later receive the inferred type of the expression. The variable is created in the current region. After that, a new type region is entered, by begin_def(), and the identifier timestamp clock is set to correspond to the new current_level. (The timestamp clock is advanced right before a new identifier is created. That's why Ident.set_current_time receives ty.level rather than the incremented current_level as the argument.) Any type constructor declared within the the local module will hence have the binding time of current_level or higher. Ctype.init_def(Ident.current_time()) sets the type level to be the binding time of the last identifier of the local module. Therefore, all fresh types created afterwards, when type checking the body, will have the level greater or equal than the binding time of any local module's type constructor. The unification will watch that any level update preserve the invariant. Finally, the unification with ty at the very end (whose region, recall, is outside the let module's region) will make sure than none of the local type constructors escape through the return type.

Incidentally, Typetexp.narrow () and Typetexp.widen context in the above code establish a new context for type variables within the local module. That's why

     fun (x:'a) -> let module M = struct let g (x:'a) = x end in M.g
has the inferred type 'a -> 'b -> 'b rather than 'a -> 'a -> 'a. The two occurrences of 'a in the above code are the distinct type variables. A local module shares none of its type variables with the surrounding.

Existential types are quite like the types declared in local modules: in fact, existentials can be implemented with first-class local modules. Therefore, checking that types created by pattern-matching on (or, opening of) an existential do not escape the pattern-matching clause uses the same technique: see Typecore.type_cases.


Discovery of levels

Didier Rémy has discovered the type generalization algorithm based on levels when working on his Ph.D. on type inference of records and variants. (Incidentally, he calls 'levels' ranks -- alas, 'levels' is the term now used in the OCaml type checker.) He prototyped his record inference in the original Caml (Categorical Abstract Machine Language), which was written in Caml itself and ran on the top of Le Lisp. That was before Caml Light let alone OCaml. He had to recompile Caml frequently, which took a long time. As he says, the type inference of Caml was the bottleneck: ``The heart of the compiler code were two mutually recursive functions for compiling expressions and patterns, a few hundred lines of code together, but taking around 20 minutes to type check! This file alone was taking an abnormal proportion of the bootstrap cycle. This was at the time when recompiling fonts in LaTeX would also take forever, so I think we were used to scheduling such heavy tasks before coffee breaks -- or the other way round.'' The type inference in Caml was slow for several reasons. First, the instantiation of a type schema would create a new copy of the entire type -- even of the parts without quantified variables, which can be shared instead. Doing the occurs check on every unification of a free type variable (as in our eager toy algorithm), and scanning the whole type environment on each generalization increase the time complexity of inference.

Didier Rémy resolved to speed up the process. He says:

So, when I wrote my prototype for type checking records and variants (which, being structural, tend to be much larger then usual ML types), I was very careful to stay close to the theory in terms of complexity.
  • I implemented unification on graphs in O(n log n)---doing path compression and postponing the occurs-check;
  • I kept the sharing introduced in types all the way down without breaking it during generalization/instantiation;
  • finally, I introduced the rank-based type generalization.
This efficient type inference algorithm was described in Rémy's PhD dissertation (in French) and in the 1992 technical report. The sound_lazy algorithm explained earlier was a very simple model of Rémy's algorithm, representing its main features. Xavier Leroy implemented the type levels and the level-based generalization in Caml-Light. However, for various reasons he implemented the version akin to sound_eager, with the occurs check on each binding of a free type variable.

Didier Rémy prefers to view ranks, or levels, in terms of graphs. If we add to the abstract syntax tree type annotations on each node, edges for shared types and edges from a quantified variable to its quantifier, we obtain a graph. The level of a free type variable can be thought of as a de Bruijn level -- a pointer to the AST node that will quantify the type variable. That AST node must be a let node, in the Hindley-Milner system. Unifying two free variables adds a sharing edge between them, which requires the adjustment of levels to maintain the invariant that a quantifier node dominates all uses of its bound variables. (Recall, a dominator in a graph for a set of nodes V is a node d such that all paths from the root to each node in V pass through d.) Adding the sharing edge may create a path that no longer passes through the old dominator, letting the variable escape, so to speak, and become dominated by the let node with the wider scope.

The graphical view of the ranks proved fruitful. Rank-based generalization easily extends to type checking of records with polymorphic fields. Eventually this graphical view has led to MLF. Didier Rémy remarks that ``the main operation in MLF -- raising binders --is analogous to the computation of minimal rank between two nodes.'' Rémy's two MLF talks below describe the system and show several animations of rank adjustments during the type checking. He also points to the view of ranks from the point of constraint-based presentation of ML type inference, explained in ``The Essence of ML Type Inference''.

A History of Caml
< >
Section ``The first implementation'' describes the original Caml.

François Pottier and Didier Rémy. The Essence of ML Type Inference
In Advanced Topics in Types and Programming Languages (Benjamin C. Pierce, editor)
Chapter 10, pages 389-489. MIT Press, 2005.

Didier Rémy: Extension of ML Type System with a Sorted Equational Theory on Types
Research Report 1766, Institut National de Recherche en Informatique et Automatique, Rocquencourt, BP 105, 78 153 Le Chesnay Cedex, France, 1992.
< >

Didier Rémy: A new look on MLF
< >

Didier Rémy: MLF for Everyone (Users, Implementers, and Designers)
< >

David McAllester: A logical algorithm for ML type inference Proc. RTA'03, pp. 436-451
< >
David McAllester has much later re-discovered the efficient generalization. He also showed that the ML type inference is nearly linear in program size for most practical programs.

George Kuan and David MacQueen: Efficient ML Type Inference Using Ranked Type Variables
ML Workshop 2007
< >
The paper compares two level-based Hindley-Milner inference algorithms: one uses let-levels, as explained on this page, while the other relies on lambda-levels. The paper develops abstract machines for both algorithms and describes their several interesting formal properties. The lambda-level approach was used in SML/NJ.

Peter Sestoft: Programming Language Concepts
Springer Undergraduate Texts in Computer Science. xiv + 278 pages. July 2012
< >
Chapter 6 (see lecture slides and examples on the above page) describes a simpler version of Rémy's algorithm -- essentially, sound_eager.


Creating fresh type variables

The OCaml type checker provides two functions to create a fresh type variable. This section illustrates the difference between them. The functions are defined in, with the following signatures:
     newvar    : ?name:string -> unit -> type_exp
     newgenvar : ?name:string -> unit -> type_exp

Both take the optional argument ?name to give the name to the variable. The name will be chosen automatically otherwise.

The function newvar creates a variable at the current_level whereas newgenvar creates at the generic_level. In the code

     let ty1 = newvar () in
     unify env ty1 some_type
     let ty2 = newgenvar () in
     unify env ty2 some_type
both ty1 and ty2 behave the same: the type variable will be bound to some_type. Since the current_level corresponds to the innermost alive region, some_type's level is the current level or smaller, and so remains unchanged in either case.

The difference emerges in the following two snippets (the second often occurs in

     let ty1 = newvar () in
     let list_type = newgenty (Tconstr(p_list, [ty1])) in
     let texp = instance env list_type in
     unify env texp some_type
     let ty2 = newgenvar () in
     let list_type = newgenty (Tconstr(p_list, [ty2])) in
     let texp = instance env list_type in
     unify env texp some_type
The function instance copies the type -- creates a Tsubst node, to be precise, only if the type is generic. That is, in
     let ty = newvar () in instance env ty
instance acts as the identity function. However, in
     let ty = newgenvar () in instance env ty

instance copies the variable. Therefore, in the first snippet above, unify at the end may affect the list_type, by instantiating ty1. The list_type cannot possibly be affected in the second snippet since unify will act on the copy of ty2.


The true complexity of generalization

The let-generalization in OCaml is far more complex than what we have sketched earlier. This section is to help appreciate the true complexity of generalization.

The let-expression in OCaml has the general form

     let [rec] pattern = exp and pattern = exp ... in body
The let type checker type_let -- 160 lines of code in, not counting the type checking of patterns -- receives the list of pattern-expression pairs, and the recursion-flag. Here is the end of its code
     begin_def ();
     let exp_list =
        (fun (spat, sexp) (pat, slot) -> .... (* type checking of expressions *)
          type_expect exp_env sexp pat.pat_type)
        spat_sexp_list pat_slot_list in
       (fun pat exp ->
          if not (is_nonexpansive exp) then
            iter_pattern (fun pat -> generalize_expansive env pat.pat_type) pat)
       pat_list exp_list;
       (fun pat -> iter_pattern (fun pat -> generalize pat.pat_type) pat)
     (List.combine pat_list exp_list, new_env, unpacks)
We see the familiar pattern:
     begin_def(); ... newvar () ... end_def(); generalize
But there is another traversal of the type, with generalize_expansive. That function is invoked only if the expression is expansive, that is, may have a visible effect -- for example, it is an application. The function Ctype.generalize_expansive traverses its argument type_expression; when it comes across a constructed type Tconstr(p,args) (such as the list type, etc), and is about to traverse an arg, generalize_expansive checks the declaration of the type p for the variance of that argument. If arg is covariant, generalize_expansive traverses arg and sets the levels of the components above the current_level to the generic_level. If arg is not covariant (e.g., the argument of ref and array type constructors), arg's components with the levels above the current are set to the current_level. The subsequent generalize will leave those levels as they are. This is how a so-called relaxed value restriction is implemented, which is responsible for inferring the polymorphic type for
     # let x = (fun y -> print_string "ok"; y) [];;
     val x : 'a list = []
Here, x is bound to an application, which is not a syntactically value and which is expansive. Its evaluation certainly has a visible effect. And yet the type of x is generalized because the list type is covariant in its argument. SML would not have. Without the relaxed value restriction, MetaOCaml will be hardly usable. For example,
     let x = .<1 + .~(...)>.
is an expression, so the classifier cannot be generalized and hence x cannot be run.
Jacques Garrigue: Relaxing the Value Restriction
FLOPS 2004, pp. 196-213

Last updated March 7, 2013

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