By Sami Beydeda, Matthias Book, Volker Gruhn
Abstraction is the main uncomplicated precept of software program engineering. Abstractions are supplied by way of versions. Modeling and version transformation represent the middle of model-driven improvement. versions might be subtle and at last be reworked right into a technical implementation, i.e., a software program system.The objective of this ebook is to provide an outline of the state-of-the-art in model-driven software program improvement. Achievements are thought of from a conceptual perspective within the first half, whereas the second one half describes technical advances and infrastructures. eventually, the 3rd half summarizes studies received in genuine tasks utilising model-driven development.Beydeda, ebook and Gruhn prepare the implications from top researchers during this zone, either from and academia. the result's a suite of papers which provides either researchers and graduate scholars a finished evaluate of present learn concerns and commercial vanguard perform, as promoted through OMG's MDA initiative.
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Extra resources for Model-Driven Software Development
This scheme is introduced in the following section and is followed by examples for its application in Sect. 3. 1 Fine-Grained Classiﬁcation Scheme In this section, a ﬁne-grained classiﬁcation scheme is introduced that considers the possible variations of the systems, the potential changes of models, and the variations in the respective formalisms. To begin with, Fig. 2 shows an overview of the identiﬁed types of transformations. As the reader can observe, we have chosen a very simple scheme for naming the different types of transformations by following the graphical layout of the ﬁgure, which should be easy to remember.
Our approach allows a rather ﬂexible treatment of the communication since the UMS main loop (Fig. 2) can be modiﬁed as necessary. For example, our explicit way of modeling the communication links and the messages exchanged over them allows modeling exterior inﬂuence on the communication within a system (such as attacks on insecure connections, or quality-of-service aspects of networks). outQuA outQuA := ∅ Fig. 1. Behavior of a UML Machine 40 Jan Jürjens and Pasha Shabalin Deﬁnition 3. A UML Machine System (UMS) A = (NameA , CompA , SchedA , LinksA , MsgsA ) is given by • a name NameA ∈ UMNames, • a ﬁnite set CompA of UML Machines called components, • a UML Machine SchedA , the scheduler that may call the components as subroutines, • a set LinksA of two-element sets l ⊆ CompA , the communication links between them, and • a set of messages MsgsA ⊆ MsgNm that the UML Machine System is ready to receive.
The inﬁnite queues are approximated by ﬁnite queues. Especially in reactive systems that are executed on hardware platforms with only small data memories, memory overﬂows can easily occur that cannot be attributed to an error in the speciﬁcation. D. thesis (, pp. 179–180), depicts this situation in more detail (see Fig. 6). Using the timer perT, the sensor process periodically measures a certain physical value that is sent to the logger process. Initially this process is in the producerA a) consumer go go producerB producerA b) sigB /* lost */ idle sigA consumer go go producerB idle sigA receiving receiving sigB Fig.