Compositional Interchange Format for HybridSystems (CIF
The main purpose of the Compositional Interchange Format (CIF)[1], that hasoriginally been developed in HYCON, see [2] and [3, 4, 5, 6], is to establishinter-operability of a wide range of tools by means of model transformations toand from the CIF. In addition, the CIF provides a generic modeling formalismand tools for a wide range of untimed, timed and hybrid systems. An overviewon previous related work on interchange formalisms, such as found in [7], [8],[9], can be found in [3, 4].
The concepts in the CIF and the relations between them are defined in a
so-called conceptual or meta model, see [1]. This model is defined in terms of(Ecore) class diagrams [10]. From these class diagrams, XML Schema definitions(XSDs) [11] have been generated. The XML Schema definitions as well as theEcore models can be obtained electronically via [12].
Regarding concrete syntax and behavioral semantics, the CIF consists of an
abstract format, which is specified using a mathematical notation and is usedfor the definition of the formal semantics, and a concrete format, as definedin [5], which is specified in the ASCII character set by a formal grammar andis used as a modeling language. The operational semantics of a model in theabstract format is defined formally in a SOS style [13]. It defines the math-ematical meaning of a hybrid model in terms of an hybrid transition system. The semantics of a model in the concrete format is formally defined by meansof a mapping to the abstract format. The advantage of having two formats isthat each can be tailored to its specific purpose. In general, the abstract formathas fewer concepts in order to simplify the semantics, while the concrete formathas ‘syntactic sugar’ and more emphasis on backward compatibility in order tofacilitate modeling. In [14], the concepts of the (concrete) CIF are illustratedby means of a hybrid model of a supermarket refrigeration system that exhibitsboth, nonlinear DAE dynamics as well as significant discrete dynamics, andserves as a challenging case study for hybrid control techniques in several Euro-pean research projects. More information about CIF and CIF tools allowing,
e.g., simulation and visualization, can be found in [12].
The CIF serves as the basis of the European research project MULTIFORM,see [15]. The main objective of this project is to develop interoperability oftools and methods based on different modeling formalisms to provide integratedcoherent tool support for the design of large complex controlled systems. WithinMULTIFORM, algorithms and tools for the translation to/from the CIF willbe defined for a large variety of modeling languages, including Chi, gPROMS,Matlab/Simulink, Modelica, MUSCOD-II, PHAVer, and UPPAAL.
Depending on the availability of a formal definition of the behavioral se-
mantics of a language, two different categories of transformations can be distin-guished:
• Transformations from formalisms that have formal semantics to the CIF (vice
• Translations from formalisms that do not have formal semantics to the
Transformations between formalisms with formal se-mantics
In case of a translation where the source formalism as well as the target for-malisms have formal semantics, one can define an equivalence relation 1 betweenthe semantics of the two formalisms. By means of mathematical proof, it canbe shown that the behavior of an input model and the behavior of the outputmodel of the translation are equivalent.
To illustrate this approach, consider the translation of hybrid automata [16]
to the CIF. The semantics of a hybrid automaton is a timed transition sys-tem with two types of transitions: action transitions (corresponding to controlswitches) and time transitions (corresponding to continuous behavior in a con-trol mode). On the other hand, the semantics of a CIF automaton is a hybridtransition system which also has these two types of transitions. The main differ-ence between these semantics is in the labeling of the action and time transitions. In timed transition systems the labels of action transitions are simply the eventsof the hybrid automaton, whereas the labels of the action transitions of a hybridtransition system also contain the valuations of the model variables prior to andafter the action. For time transitions, the labels in a timed transition systemcontain only the duration of the time transition whereas time transitions in hy-brid transition systems also have the trajectory of the model variables as a label. Finally, a timed transition system can have many initial states whereas a hybrid
1In fact multiple equivalence relations can be defined depending on the properties to be
transition system has only one initial state. This one initial state captures thebehavior of all the initial states of the timed transition system.
Let ¯h be a mapping that maps a hybrid transition system onto a timed
transition system by removing valuations from action transitions and trajecto-ries from time transitions. Furthermore, let HA be a hybrid automaton and letMCIF be the CIF specification associated to it by its translation. Furthermore,
let TTS and HTS be the semantics of HA and MCIF, respectively.
Then, there exists a (strong-)bisimulation relation [17, 18], denoted by ↔ ,
between the states of TTS and the states of ¯
from an initial state of TTS can be simulated by the initial state of ¯
and each transition from the initial state of ¯
Examples of similar translations including their correctness proofs can be
found in [19, 20] (Translation of χ to 1) piecewise affine systems and 2) hybridautomata), and [21, 22] (Translation of χ to UPPAAL).
Transformations between formalisms with formal se-mantics
In case of a translation where the source formalism does not have a formal se-mantics and the target formalism has a formal semantics, then, by means of a(formally defined) translation, formal semantics is given to the source formal-ism. An example of this approach can be found in [23] that defines bidirectionaltransformations between gPROMS and Modelica via the CIF. The correct-ness of the translations has been validated by means of comparing the simulationresults of several input models and their respective output models.
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