-Even if they exhibit differences, many DomainSpecific Modeling Languages (DSMLs) share elements from their concepts, notations and semantics. StateCharts is a wellknown family of DSMLs that share many concepts but exhibit notational differences and many execution semantics variants (called Semantic Variation Points - SVPs -). For instance, when two conflicting transitions in a state machine are enabled by the same event occurrence, which transition is fired depends on the language variant (Harel original StateCharts, UML, Rhapsody, etc.) supported by the execution tool. Tools usually provide only one implementation of SVPs. It complicates communication both between tools and end-users, and hinders the co-existence of multiple variants. More generally, Language Workbenches dedicated to the specification and implementation of eXecutable Domain-Specific Modeling Languages (xDSMLs) often do not offer the tools and facilities to manage these SVPs, making it a time-consuming and troublesome activity. In this paper, we describe a modularized approach to the operational execution semantics of xDSMLs and show how it allows us to manage SVPs. We illustrate this proposal on StateCharts.
Domain-Specific Modeling Languages (DSMLs) provide
user-friendly abstractions for domain experts who are not
necessarily well-versed in the use of programming languages even
when limited to domain-specific libraries (i.e., API dedicated
to a domain like security, fault tolerance, etc.). A DSML is
called executable (xDSML) when it represents systems which
evolve during time (i.e., it captures the behavior(s) of the
systems). Being domain-specific eases the design of complex
software-intensive systems whereas being executable enables
early verification and validation of the systems [
Semantic Variation Points (SVPs) are language
specification parts left intentionally under-specified to allow further
language adaptation to specific uses. SVPs must be dealt with
either through further refinement of the language specification
(in the case of UML, through stereotypes or profiles) or by
making arbitrary choices in the implementation. The latter
is most often the case when accommodating specific types
of execution platform (e.g., distributed, highly-parallel, etc.),
allowing various implementations of the concurrency concerns
(e.g., parallelism or thread interleaving). For instance, the
concurrency in CPython, the reference implementation of Python,
is subject to the Global Interpreter Lock (GIL), which prevents
multithreaded programs from taking advantage of
multiprocessor systems; while Jython, the Java implementation of Python
supports parallelism through the Java Virtual Machine (JVM).
Another example is fUML [
SVPs are usually identified informally in the DSML syntax and semantics specification documents. In the context of this paper, we will draw the difference between a Language (the specification of a syntax and of a semantics that may contain SVPs) and its Dialects (which implement a language, making choices about some – possibly all – SVPs of the language). Tools commonly only provide one dialect, thus constraining the end-user to work with the selected specific implementation of SVPs, which may not be the best-suited for their needs. Besides, it also complicates the cooperation between tools, since they may implement SVPs differently, giving a different semantics to the same syntax. Two engineers with different backgrounds may also assume different meanings for the same model, which impairs communication. Finally, large projects may need to use several dialects cooperatively, which means that this issue cannot be simply reduced to the choice of a unique tool: one dialect with an associated tool may be the best fit for a particular aspect of a system, but other ones may be better-suited for other aspects of the system.
This paper describes an approach to the specification of the
execution semantics of an xDSML that eases the specification
and management of SVPs. The approach is implemented in the
GEMOC Studio1. It is illustrated with Finite State Machines
(FSMs), a common formalism to represent complex system
behaviors. StateCharts [
Modern systems (IoT, etc.) increasingly rely on concurrency, and modern platforms provide more and more concrete concurrency facilities (many-core, GPU, etc.). xDSMLs must provide sophisticated concurrency concepts with well-defined semantics, to enable early concurrency-aware analyses, and
SVPs related to the concurrency concerns to allow
refinements to specific platforms. But the concurrency concerns
and SVPs of xDSMLs are usually implicit, embedded in the
underlying execution environment or in the meta-languages
used to define the xDSMLs. The GEMOC executable
metamodeling approach makes explicit the concurrency aspects
in an xDSML specification, relying on event structures [
This paper is structured as follows: Section II summarizes the StateCharts example. Section III describes the GEMOC executable modeling approach and illustrates how it is particularly suitable for the specification of SVPs. The implementation in the GEMOC Studio is described in Section IV. Finally, Section V gives related work and Section VI concludes and proposes insights on future works.
II. SEMANTIC VARIATION POINTS OF STATECHARTS
The StateCharts formalism is an extension of Finite State
Machines (FSMs) with hierarchy, concurrency and broadcast
communications [
In StateCharts, an FSM is composed of Regions and Events. Each Region is composed of States and Transitions between these States. A State can be composed of Regions, thus defining a hierarchy between the States. Each Region has an initial State. A Transition can have a Guard (predicate expression) and an Effect (collection of behavior expressions named Actions). A Transition has a Trigger which is a reference to an Event.
The bulk of the semantics is common to all three StateCharts dialects. When an Event occurs, it enables all the Transitions whose Trigger references the occurring Event. Depending on their Guard evaluation result, they may then be fired. When a Transition is fired, its source State is exited, its Effect is executed and its target State is entered.
Simultaneous Events: Can different Events occur at the same time? In the original formalism, they can, and they are dealt with simultaneously (concurrently). The UML formalism adheres to the concept of run-to-completion (RTC) which means that Event occurrences are handled one by one (possibly with priorities), thus simultaneous Events are not allowed.
Order of execution of Actions: When a Transition is fired, how are the Actions that compose its Effect executed? In parallel in the original formalism and in sequence in the UML version.
Priorities of conflicting Transitions: When several Transitions are enabled by the same Event occurrence, how are they handled if their executions conflict (e.g. their application would lead to an inconsistent model state) ? In the original formalism, priority is given to the Transition which is highest in the hierarchy, while in UML, priority is given to the Transition which is lowest in the hierarchy.
Let us consider the example model from Figure 1, representing a simple music player.
The following scenarios illustrate the 3 targeted SVPs: When in State “Off”, “StartEvent” and “StopEvent” occur.
– Original: they are dealt with concurrently, resulting in the Transition from “Off” to “On” being fired. – UML: not supported.
When, in States “On” and “Paused”, the Event “StartEvent” occurs (assuming x and y both start at 0), triggering the firing of the Transition from “Paused” to “Playing”.
– Original: when reaching State “Playing”, the values of x and y are respectively 1 and 0. – UML: when reaching State “Playing”, the values of x and y are respectively 1 and 1.
When, in States “On” and “Playing”, the Event “StopEvent” occurs.
– Original: the Transition from “On” to “Off” is fired. – UML: the Transition from “Playing” to “Paused” is fired.
So far, these differences have to be deduced from the documentation of the respective tools or specifications, or through tests of the tools. It is not explicit, when considering the model, what the associated version of the semantics is. III. CONTRIBUTION AND APPLICATION TO STATECHARTS
This section describes the GEMOC executable metamodeling approach and how we propose to deal with SVPs. We illustrate it on StateCharts.
The language and modeling communities specify languages
with an Abstract Syntax (AS), one or more Concrete Syntaxes
(CSs) and mappings from the AS to one or more Semantic
Domains (SDs) [
The Semantic Rules specify the sequential evolutions of the model state at runtime (not to be confused with StateCharts States). The Execution Data (ED) represent at the language level the runtime state of the model. Execution Functions (EF) specify how the ED evolve during execution. For instance, a Region has a “currentState” reference in its ED which represents its current State during the execution. It is updated by the EF “fire” on Transitions.
The Concurrency Model is captured by the Model of
EventType structure, specifying at the language level how, for
a given model, the event structure [
The full semantics is built thanks to the Communication Protocol which maps some of the EventTypes from the MoCC to the EFs. This means that, at the model level, when an event occurs, it triggers the execution of the associated EF on an element of the model. For instance, if the Communication Protocol specifies that the EventType “et FireTransition” is mapped to Transition::fire(), then the event “e FireOn2Off” (instance of “et FireTransition” for the Transition from “On” to “Off”, “On2Off”) triggers the execution of On2Off .fire(). Figure 4 shows the different concerns, at the model level, of our example: the bottom part of the Event Structure (MoCC at the model level), the Execution Functions and the Communication Protocol (both at the model level). The
Communication Protocol allows the MoCC and the Semantic Rules to remain independent, enabling modular changes in either part.
If several execution paths are allowed at a point in the event structure, it means that there is either Concurrency or Conflict. The first one means that other events are happening concurrently (interleaved or in parallel), in which case the execution paths will eventually merge. It does not mean that the executed model reaches the same state, but instead that in terms of pure control flow (independent of any data from the model) it is at the same point in the execution. Our example model is sequential, so there is no need for parallelism or interleavings. The second one means that there is a disjunction among the possible execution paths, which ultimately results in different final configurations of the event structure. Conflicts are a sign of nondeterminism in the semantics of the language, which means that either the language is indeterministic by intention, or that there is a SVP pertaining to the concurrency concern of the language. In the case of StateCharts, depending on the Events occurring, the execution will go one way or another, therefore there are many conflicts to represent the possible inputs (Events occurring).
SVPs can occur in any parts of the execution semantics.
The ones in Semantic Rules target the model runtime state representation and/or evolution. For instance, changing a List into a Stack to have a LIFO policy instead of FIFO, or incrementing a value twice instead of once to double a ressource consumption. In StateCharts, a Transition Effect is a collection of Actions executed in parallel (in the original formalism) or in sequence (in UML). This SVP can be implemented in the EF that executes the Effect of the Transition being fired, with a parallel or sequential implementation. Another solution consists in providing both versions of the EF, but in changing the Communication Protocol to use the sequential one or the parallel one depending on the dialect we wish to use. The imperative nature of these implementations makes them complex to manage.
Thus, we propose to rely on the language’s declarative MoCC to represent the superset of possibilities for all allowed concurrency-related SVPs, and to refine the MoCC for each dialect by removing the execution paths that do not correspond to the expected semantics. Nondeterminisms in the MoCC (resulting in conflicts in a model event structure) can be seen as potential SVPs. SVP implementations restrain the number of outgoing execution paths at a conflict point. In StateCharts (where a scenario, user, or environment drives the execution), there will be a lot of nondeterminisms left in the MoCC even after implementing the SVPs of the various dialects (to represent the possible inputs, Events being allowed to occur at every step of the execution). SVP implementations cannot add new EventTypes in the MoCC, as it would result in new execution paths that were not initially present in the language’s MoCC specification.
For instance, let us consider the SVP concerning simultaneous Events. The part of the event structure corresponding to this situation is represented in Figure 5. For this particular
SVP, the UML dialect implements a subset of the original formalism’s possibilities. Individual Events “e StartEvent” and “e StopEvent” are possible in both situations, but having both “e StartEvent” and “e StopEvent” is only allowed in the original formalism. The part of the MoCC responsible for implementing this SVP in UML is an extension of the part of the MoCC for the original formalism, with the addition of a constraint preventing simultaneous Event occurrences.
The SVP concerning conflicting Transition is different: there is a disjunction between the original formalism and the UML one. Figure 6 shows an example event structure of a situation where, in the State “On” and “Playing”, the Event “StopEvent” (or both “StartEvent” and “StopEvent”) occur. In this case, the original formalism gives priority to “On2Off”, while UML gives priority to “Playing2Paused”. Therefore, the MoCC of the language representing the superset of possibilities for all allowed variants must allow both solutions. Each dialect then extends the MoCC of the language to add constraints resulting in the removal of some of the execution paths not corresponding to the implemented semantics.
The difference between specializing a language for a specific environment and implementing a Semantic Variation Point is blurry. SVPs sometimes represent adaptation points for a specific platform (distributed, highly parallel, . . . ). Therefore the event structure used to define the concurrency concerns in the semantics of xDSMLs is also a good fit for defining a language while still allowing dialects to be implemented by extending the concurrency model. SVPs can also be implemented in a modular way so that dialects are then realized by merging specific SVP implementations; similar to creating a new class in Aspect-Oriented Programming by extending an existing class and weaving existing aspects onto it.
MoCC. The definition of the EventType structure relies on
the Event Constraint Language (ECL) [
Listing 2 EXCERPT FROM THE MOCC OF THE UML DIALECT OF STATECHARTS
SPECIFIED USING ECL. THE ADDITIONAL CONSTRAINT “NOSIMULTANEOUSEVENTS” IMPLEMENTS THE SIMULTANEOUS EVENTS
SVP. 1 import ’platform:/resource/org.gemoc.sample.
statecharts.model/model/statecharts.ecore’ 2
IV. IMPLEMENTATION 43 -co-ntDexetfiSntiantgeMtahcehiEnveentTypes in their context
The GEMOC executable metamodeling approach is imple- 5 def: mocc_initialize : Event = self
omnenptreedviionusa wlaonrgku[a1g0e].wIotriksbinetnecghr,attehde iGnEthMeOECcliSptsuedMio2odbealsinedg 876 codnetfe:xtmoTcrca_nfsiirteio:n Event = self
Framework (EMF) [
The AS is specified with Ecore, the Eclipse Modeling 10 context StatechartEvent
11 def: mocc_occur : Event = self
Framework implementation of EMOF, and with the Object 12
Constraint Language (OCL) for the static semantics. Both 13 -- Constraint for UML
EMOF [
The EFs are implemented with the Kermeta 3 Action
Language (K3AL) [
K3AL, just like xTend, compiles into Java Bytecode and provides an executor based on the Java Reflection API to dynamically execute the EFs. Listing 1 shows the implementation of the StateMachine.initialize() Execution Function in K3AL.
cation Language (CCSL) [
The Communication Protocol is specified using the Gemoc
Events Language (GEL) [
At runtime, an Execution Engine written mostly in Java coordinates the K3AL interpreter, the GEL interpreter and the CCSL solver to execute a model. Figure 7 shows the sequence diagram for an execution step. First, the Execution Engine retrieves from the CCSL Solver the next set of possible configurations (scheduling solutions). Its heuristic Listing 1 IMPLEMENTATION OF THE EXECUTION FUNCTION ”INITIALIZE” OF
STATEMACHINE IN KERMETA 3. 1 @Aspect(className=StateMachine) 2 class StateMachineAspect { 3 // Initializes each Region with its initial state 4 def public void initialize() { 5 self.regions.forEach [ region | 6 region.currentState = region.initialState 7 ] 8 } 9 }
MoCCML [
Listing 3 EXCERPT FROM THE COMMUNICATION PROTOCOL OF STATECHARTS
SPECIFIED USING GEL. 1 DSE InitializeStateMachine: 2 upon mocc_initialize 3 triggers StateMachine.initialize 4 end 5 6 DSE FireTransition: 7 upon mocc_fire 8 triggers Transition.fire 9 end then selects one solution among the possible ones. A default implementation consists in letting the user do the selection to manage indeterministic situations manually when developing an xDSML. Based on the Communication Protocol, the set of EFs to execute is deduced from the selected solution. All the EFs are executed in parallel, resulting in an updated runtime state of the model.
Figure 8 gives the architecture of our implementation of StateCharts.
The modularization of our approach effectively allows the reuse of part of the operational semantics (in our case, of the ED and EFs and of parts of the Communication Protocol and of the MoCC) for the various dialects of StateCharts.
To implement our second SVP, “Communication Protocol for UML” maps “Transition.executeEffectSequentially()” while for original StateCharts, “Transition.executeEffectInParallel()” is mapped. In “UML StateCharts MoCC”, a constraint is added to exclude simultaneous occurrences of Events (as shown in Listing 2). Priority is given to the inner Transition in case of conflicting Transitions (third SVP) while the “Original StateCharts MoCC” gives priority to the outer Transition.
DMSL editors, also called Language Workbenches [
Semantic Variation Points (SVPs) are usually poorly identified in language specifications, and their implementations are often hardcoded into the implementing tools, hindering the end-users from choosing their own variation of the language, particularly one that may be a better fit for a particular class of problems. The GEMOC executable metamodeling approach separates the semantic mapping of xDSMLs to make explicit the Concurrency Model, completed by Semantic Rules describing how the runtime state of the model evolves, and by a Communication Protocol to connect both. Its event structure-based approach to the concurrency model eases the specification of nondeterministic situations, corresponding to potential SVPs. Implementing a SVP is then done by extending the concurrency model with additional constraints, resolving partially or totally nondeterminisms that were left in the language’s Concurrency Model. The SVP implementations are thus weaved into the language definition, allowing the execution tool to remain independent from any arbitrary choice with regards to the SVPs. Future work will be concerned with adding the possibility to hinder parts of the concurrency model of the language from being extended by dialects. So far in our approach, every point of nondeterminism left in the concurrency model is considered as a potential SVP. But sometimes, the nondeterminisms left in the concurrency model are integrally part of the semantics of all variants allowed and should not be extended and resolved by dialects. We also plan to consider the case of SVPs which spread through the three units constituting the semantics (Concurrency Model, Semantic Rules or Communication Protocol) because so far, we have only considered SVPs which are contained in only one of these units. At last, we target the integration of these proposals with SVPs at the syntax level, both abstract and concrete; and to experiment the use of variability management techniques to make the management of language variants more explicit.
This work is partially supported by the ANR INS Project GEMOC (ANR-12-INSE-0011).