Automatic program transformation and generative programming aimed
at increasing programmer productivity by automating the programming tasks using
some sort of automatic program generation or transformation, such as code
generation from a domain-specific language, aspect weaving, optimization,
specialization or a generic program in a specific context. Key to achieving
this goal is the construction of tools to automate transformations do. If
generative programming has become a staple part of the process of software
engineering, the construction of generative instrument themselves become
automated as possible. It requires an infrastructure with support for common
tasks in the construction of the transformation of the system. The top is
actually changing systems such as compilers and language extensions, static
analysis tools, and aspect weavers. These functions are implemented as tool
compositions from the lower layers expanded to include part of the
implementation of certain transformation in question.
Syntactic transformation is the syntactic transformation that
provides addresses displayed address to be generated at runtime consists of a
list of symbols. Transformation is designed to provide the program code as a
new symbol is added to the front of the list, when the stack is expanded to
change. This transformation has two main parts: First, change every function
definition so that the function takes one argument, the address. Secondly,
every function application to change the current address is extended with a
unique symbol (syntactic) application recognized within the program and gives
it as an argument changed address is used as the function.

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Program transformations are used algorithm design integration program
development. This will lead to a better understanding of some known algorithms
and the discovery of new algorithms. The next step is to program transformation
technology will gradually develop good execution of the known data structures.
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Program transformations allow us to replace some of the other
programs. For these healthy it is important to maintain transformations semantics
of the original program. We also need strategies to have directed the
application of the rule changes to achieve goals such as efficiency improvements,
higher levels of parallelism, better modularity etc.
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Traditionally, the program transformations used to improve the efficiency
of the programs on a single machine. When the program complex parallel and
distributed systems, we need tools for automated mapping program architecture.
Sophisticated transformations are required to improve the performance of the entire
system; there may even be such transformations must be dynamic by which to
apply the adjustment program a constantly changing environment.
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