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Overview
Analysis of source code or model with code rules can be described as a two-phase process.
In the first phase, the languages used by the model being analysed, and their prototypes (meaning the languages that are being extended, but not used directly) are surveyed for the appropriate code rules aspect model, which is types in case of type checking, for example. Contents of this aspect model is a contribution of this particular language. All rules within this model are applied to the source model, with rules coming from extension languages having higher priority.
The outcome of this phase is a constraints program, which is a collection of handlers, which in turn represent lists of productions. This «program», however, exists in memory only, it does not have any textual representation. Aside from generating productions, the rules can also process the model normally, reporting errors as usual.
The first phase runs in «read action», therefore blocking potential writes, which means the editor may become unresponsive if a write action is requested. Ideally the rules should finish quickly and postpone all heavy load to the next phase, which can be run in the background, as the access to SModel is no longer necessary.
In the second phase the constraints program that was created in phase one is evaluated. Evaluation starts with a query, which serves as an entry point to the program. For example, type system defines TYPECHECK and CONVERT queries, aimed at running type checking and testing if a type can be converted to another type, correspondingly. Queries are declared in the same aspect model.
(example of a query)
In the above example, the query defines two logical variables (A and B) of type term, which serve to represent types internally. First, both query parameters to and from are expanded, meaning that their SNode representations are converted to terms, and then the constraint convertsTo(A, B) is activated, kicking off the process of evaluating the program. In case productions triggered by convertsTo/2 constraint all evaluate to true, the query is deemed successful, and if there is at least one production that evaluates to false, the query fails accordingly.
One nice feature of using code rules is the ability to abstract away from type structure defined by the language. For example, one may decide to represent all primitive types as a term primitive(kind=<specific kind>). Terms can also incorporate values as regular Java objects, so creating an inference rule which checks if a particular constant fits the given type, be it an int or a char, is trivial.
Having an internal representation for types also means, that if type system is required to represent types as instances of SNode to the user, this has to be addressed by the query design. For instance, a type checking query may consist of two constraint activations:
(example of a query production)
Here, the first constraint checkAll/0 fires type checking, whereas the second recoverAll/0 is responsible for restoring terms to SNode instances and reporting them back to the user. Joining the two constraints with a conjunction establishes the order in which these are evaluated.
An of course, if something can go wrong, it will. In case type inference is unsuccessful, the second stage has no chance of being evaluated. To account for that, a partial backtracking was added to the language of production templates, which helps recover from certain failures.
(example of a query production with alternative body)
Here, recoverAll/0 constraint is moved out to an «alternative branch» of production body, which allows it to be activated even if there was an error while processing the main branch.
To illustrate how automatic binding of logical variables work, consider the following example. Constraint typeOf/2 associates a type with a location in source model, and convertsTo/2 ensures its 1st argument can be converted to the 2nd, which must both be types.
(example of rule with production)
This production is triggered when both locations referred to by ae.lValue and ae.rValue have their types assigned, as both typeOf/2 constraints must be present for a match to be successful. Once production’s head is matched, both logical variables LType and RType become bound to whatever was the 2nd argument of either occurrences of typeOf/2 constraint.
It’s important to note, that although on successful match both lValue and rValue have types, it’s not guaranteed that these types are ground. A type may be represented by a free logical variable, or a term containing free variables. Another very important thing to notice is that a logical variable enjoys full privileges of being an argument to a constraint. Which means, if in the above example both variables are free, and LType = RType, then both locations will have essentially the same type (in the sense of «same instance»), not just matching types.
The following example illustrates the use of pattern matching in production’s head. Here the first argument to constraint convertsTo/2 in the head is a logical variable with pattern expression. In this case the production will only be triggered if the active constraint’s first argument is bound (is not a free logical variable), and it matches the pattern.
(example of rule with production)