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Representing and Operating with Model Differences

Representing and Operating with Model Differences. Jose E. Rivera, Antonio Vallecillo Universidad de Málaga, Spain TOOLS Europe 2008, Zurich. Introduction. Model-Driven Software Development (MDSD) Models are the key artifacts

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Representing and Operating with Model Differences

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  1. Representing and Operating with Model Differences Jose E. Rivera, Antonio Vallecillo Universidad de Málaga, Spain TOOLS Europe 2008, Zurich

  2. Introduction • Model-Driven Software Development (MDSD) • Models are the key artifacts • Most of the efforts are currently on the definition of models, metamodels and transformations between them • Other model operations (e.g., model subtyping, model difference) are required in MDSD practices • Model difference • An essential operation in several software development processes: • Version and change management • Software evolution • Model/data integration • etc. TOOLS Europe 2008

  3. MAUDELING Model difference solutions • Previous approaches: • Edit scripts and coloring techniques: • Do not produce models as results • Do not fulfill other interesting properties (composability…) • Based on text, data structures or models • Usually restricted to a specific metamodel (UML) • Our approach: • Model-based: • Differences are models, conforming to a metamodel • Metamodel independent • Self-contained, compact, composable, applicable to models conforming to different metamodel • Implementation available integrated in Eclipse TOOLS Europe 2008

  4. Model comparison 1) Matching • Finding different objects from the two models that represent the same element • The result is a model: 2) Differencing • Makes use of matching models to detect modified elements • The result is a model: Benefits: • Self-contained • Compact • Independent of the metamodel • of the source models TOOLS Europe 2008

  5. Matching Objects • Option 1:Using object persistent identifiers  Matching process is simple and robust  But not always feasible! • Option 2: Using structural similarities  Allows comparing models… • that do not use persistent object identifiers • conforming to different metamodels • that have evolved independently  Harder to define and implement • You need an algorithm to identify the matches  TOOLS Europe 2008

  6. MAUDELING The Matching Algorithm • Compares objects independently of their depth in the containment tree • Implies more comparisons • ...but brings very interesting advantages: • Moved elements through different levels can be detected; • Example of refactorization-> adding packages • Failing to identify a match does not condition other potential matches below in the tree hierarchy • Implemented in Maude TOOLS Europe 2008

  7. The Matching Algorithm • Comparing two objects: • Class rate: • Name rate: TOOLS Europe 2008

  8. Matching Algorithm: Structural rate • Structural rate depends on the type of the feature • Boolean attributes and enumerations match (with rate = 1.0) if they have the same value (otherwise rate = 0.0) • String attribute values distances are calculated using the Levenshtein distance • Numerical attribute values match rate is computed with a relative distance function (1-|n-m|/|n+m|) limited to [0..1] • References are matched recursively, i.e., objects referenced are compared using the same match operation but without taking into account their own references (to avoid cycles) • If the upper cardinality is greater than 1 (i.e., if its value is a collection), the average rate is calculated • If a structural feature is defined only in one of the objects, a penalty is applied to the final sfRate TOOLS Europe 2008

  9. Matching Algorithm: Analysis • If (Rate > Threshold) the two objects potentially match • Initially considered (although it is fully configurable): • wc = 0.5; wsf = 0.25; wn = 0.0; Threshold = 0.66 • nameRate is used in models in which the attribute name is considered as an identifier. • If the name rate is omitted (wn=0.0), potential matches are harder: features should be more strongly related • At the end of the process, only those objects that together obtain the biggest rate are kept TOOLS Europe 2008

  10. Maude (http://maude.cs.uiuc.edu/) • Formal notation and system • High-level language and a high-performance interpreter and compiler of the OBJ algebraic specification family • Supports membership equational and rewriting logic specification and programming • Maude specifications are executable • Supported by a toolkit • Executing the specifications, model-checking, theorem proving, termination and confluence, etc. • Highly efficient and integrated with Eclipse TOOLS Europe 2008

  11. Representing Models in Maude • Maude supports OO specifications and computations • Classes:class C | a1 : S1, …., an : Sn • Objects:< O : C | a1 : v1, …., an : vn > • Messages:msg m : S1 … Sn -> Msg . • A configuration is a multiset of objects and messages that evolves by rewriting rules • Models are represented as configuration of objects Nodes Nodes’ attributes Nodes’ Edges Objects Objects’ attributes Maude Configuration of objects Multigraph TOOLS Europe 2008

  12. Representing Metamodels in Maude • Object-oriented modules (i.e., specifications) • They contain the classes to which the Maude objects belong • Models conform to metamodels by construction • Used to instantiate models, to add behavior… • Metamodels are models too! • They can be represented as Configuration of objects • The classes of such objects will be the ones that specify the meta-metamodels (for example Ecore) • Used to operate and reason about them TOOLS Europe 2008

  13. Models and Metamodels in Maude • Simple State Machine example (omod SimpleStateMachines is prSTRING . class State | name : String, stateMachine : Oid, incoming : Set{Oid}, outgoing : Set{Oid} . class StateMachine | initialState : Maybe{Oid}, containedState : Set{Oid} . class Transition | name : String, target : Oid, src : Oid . endom) membership axioms + Conforms to < ’SM : StateMachine | initialState : ’ST1, containedStates : (’ST1, ’ST2) > < ’ST1 : State | name : "St1", stateMachine : ’SM, outgoing : ’TR, incoming : empty > < ’ST2 : State | name : "St2", stateMachine : ’SM, incoming : ’TR, outgoing : empty > < ’TR : Transition | name : "Tr", src : ’ST1, target : ’ST2 > TOOLS Europe 2008

  14. Calculation of Differences op modelDiff : Configuration Configuration -> DiffModel . • Possible situations : • The element appears in both models and has not been modified • The element appears in both models but has been modified; ceq modelDiff(< O1 : C | ATTS > CONF1> < O2 : C | ATTS > CONF2, MATCHM) = modelDiff(CONF1, CONF2, MATCHM) if match(O1, O2, MATCHM) . ceq modelDiff( < O1 : C1 | ATTS1 > CONF1, < O2 : C2 | ATTS2 > CONF2, MATCHM) = < newModId(O1) : ModifiedElement | element : newId(O1), oldElement : oldId(O2) > < newId(O1) : C1 | attsDiff(ATTS1,ATTS2) > < oldId(O2) : C2 | attsDiff(ATTS2,ATTS1) > modelDiff(CONF1,CONF2,MATCHM) if match(O1, O2, MATCHM) /\ (not(ATTS1 == ATTS2) or not(C1 == C2)) . TOOLS Europe 2008

  15. Calculation of Differences • The element only appears in the minuend model; • The element only appears in the subtrahend model. • Both the minuend and subtrahend models are empty: eq modelDiff( < O1 : C1 | ATTS1 > CONF1, CONF2, MATCHM ) = < newAddId(O1) : AddedElement | element : newId(O1) > < newId(O1) : C1 | ATTS1 > modelDiff(CONF1, CONF2, MATCHM) [owise] . eq modelDiff( CONF1, < O2 : C2 | ATTS2 > CONF2, MATCHM ) = < newDelId(O2) : DeletedElement | element : oldId(O2) > < oldId(O2) : C2 | ATTS2 > modelDiff(CONF1, CONF2, MATCHM) [owise] . eq modelDiff( none, none, MATCHMODEL ) = none . TOOLS Europe 2008

  16. An Example (Subtrahend Model) < ’SM : StateMachine | initialState : ’ST1, containedStates : (’ST1, ’ST2) > < ’ST1 : State | name : "St1", stateMachine : ’SM, outgoing : ’TR, incoming : empty > < ’ST2 : State | name : "St2", stateMachine : ’SM, outgoing : empty, incoming : ’TR > < ’TR : Transition | name : "Tr", src : ’ST1, target : ’ST2 > (Minuend Model) Tr2 < ’SM : StateMachine | initialState : ’ST1, containedState : (’ST1, ’ST2) > < ’ST1 : State | name : "St1", stateMachine : ’SM, outgoing : ’TR, incoming : ‘TR2 > < ’ST2 : State | name : "St2", stateMachine : ’SM, outgoing : ’TR2, incoming : TR > < ’TR : Transition | name : "Tr", src : ’ST1 , target : ’ST2 > < ’TR2 : Transition | name : "Tr2", src : ’ST2 , target : ’ST1 > (Difference Model) < 'ST1@MOD : ModifiedElement | element : 'ST1@NEW, oldElement : 'ST1@OLD> < 'ST1@NEW : State | incoming : 'TR2 > < 'ST1@OLD : State | incoming : empty > < 'ST2@MOD : ModifiedElement | element : 'ST2@NEW, oldElement : 'ST2@OLD > < 'ST2@NEW : State | outgoing : 'TR2 > < 'ST2@OLD : State | outgoing : empty > < 'TR2@ADD : AddedElement | element : 'TR2@NEW > < 'TR2@NEW : Transition | name : "Tr2", src : 'ST2, target : 'ST1 > TOOLS Europe 2008

  17. Further Operations • Operation do • do ( Ms , Md ) = Mm . • Applies to a model all the changes specified in a difference model • Operation undo • undo ( Mm , Md ) = Ms . • Reverts all the changes specified in a difference model • Sequential composition of differences • Very useful to, e.g., optimize the process of applying successive modifications to the same model undo(do(Ms, Md), Md) = Ms . do(undo(Mm, Md), Md) = Mm. TOOLS Europe 2008

  18. “do” operation specification op do : Configuration DiffModel -> Configuration . eq do ( MODEL, < O : AddedElement | element : NEWO > < NEWO : NEWC | NEWATTS > CONF ) = < originalId(NEWO) : NEWC | NEWATTS > do ( MODEL, CONF ) . ceq do (< O : C | ATTS > MODEL, < O2 : DeletedElement | element : OLDO > < OLDO : OLDC | OLDATTS > CONF ) = do ( MODEL, CONF ) if O = originalId(OLDO) . ceq do (< O : C | ATTS > MODEL, < O2 : ModifiedElement | element : NEWO, oldElement : OLDO > < NEWO : NEWC | NEWATTS > < OLDO : OLDC | OLDATTS > CONF ) = < originalId(NEWO) : NEWC | (excludingAll(ATTS,OLDATTS), NEWATTS)) > do(MODEL, CONF) if O = originalId(OLDO) . eq do ( MODEL, none ) = MODEL . TOOLS Europe 2008

  19. MAUDELING Conclusions • Model difference definition • Independent of the metamodel of the source models • Can be fully integrated into other MDSD processes • Self-contained and compact • Applicable to models conforming to different metamodel • Suitable for composing deltas and implementing further operations on them • Results are very encouraging • Tool support: • All the difference operations implemented in Maude • Integrated in Eclipse TOOLS Europe 2008

  20. Future Work • Make Maude completely transparent to the user • Conflict detection and resolution of concurrent modifications • Improving the matching algorithm • More complex heuristics • More customizable parameters • Make model operations available via Web services TOOLS Europe 2008

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