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from system “stubs” or “skeletons” to deployable products.
Several steps are required to iteratively integrate various
concerns and to transform models until the source code is
obtained. Models are less sensitive to computing technology
and to evolutionary changes of that technology. We can have
general models describing the problem space and deriving
other distinct models representing some solutions. Platform-
specific aspects, such as the characteristics of languages, can
be integrated in subsequent steps and then performance issues
or deployment aspects can be further added. In this way,
abstraction and separation of concerns can be used in a
uniform and tool-assisted process. The need for such facilities
is increasing as the semantic gap between modeling languages
and implementation codes becomes wider-and-wider.
MDE originated in the late 1990s out of the need for
more abstract software description, and to increase software
productivity and quality. It emerged from the adoption of UML
as a standard and from research on data representation,CASE
tools,and interchange format. MDE emphasizes such concerns
as abstraction, early verification, model transformation, and
automatic code generation. MDE provides a unified formalism
with models and transformations to represent artifacts and
processes of software engineering.The ability to build readable
models is important for stakeholders to collaborate efficiently.
Models only capture single points of view and focus on some
domain concepts that are known to be easier to specify,
understand, and maintain.
Software engineering needs automation. This is a fact
learned from the history of engineering. Automation is
by far the most effective technological means for boosting
productivityandreliability.MDEprovidesautomationatevery
step of development and facilitates a progressive integration of
knowledge and platform details. The techniques and tools for
usingMDEsuccessfullyhavenowreachedadegreeofmaturity
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