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Programming approach to recover DSLs
Extensions
and improvements to MARS system
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Upcoming Events of Interest
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1. July 15,
2009: Real Poster due.
2. Project
report.
3. The 3rd IEEE
International Symposium on Theoretical Aspects of Software Engineering
will be held on July 29-31, 2009, Tianjin, China.
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The poster
proposal of TASE09 is accepted.
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Grammar Inference (GI) is the process of
learning a grammar from examples, either positive (i.e., the grammar
generates the string) and/or negative (i.e., the grammar does not
generate the string). While GI has been successfully applied to many
diverse domains such as speech recognition and robotics, its application
to software engineering has been limited. Because of the widespread use
of context-free grammars (CFGs) in software system, there is a need to
maintain and infer CFGs. The goal of the proposed research is to
investigate the applicability of GI to software engineering and
programming language (PL) development challenge problems, where GI offers
an innovative solution to the problem, while remaining tractable and
within the scope of that problem. Specifically, the following challenges
are proposed for investigation:
1.
Recovery of domain-specific language (DSL)
specification
from example DSL
programs.
2.
Recovery of a metamodel from instance models.
Acknowledgement: This
material is based upon work supported by the National
Science Foundation under Grant
No. 0811630. Any opinions, findings, and conclusions or
recommendations expressed in this material are those of the author(s) and
do not necessarily reflect the views of the National Science Foundation.
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MARS with
Extension
With the
rapid development of model-driven engineering, modeling has become a
widely used software development technique. Metamodels define the syntax
of models and are needed to load model instances into a modeling tool. As
a metamodel undergoes frequent evolution, previous model instances may
become orphaned from the new definition. The metamodel may also be lost,
resulting in the inability to load and view existing model instances.
MARS, a metamodel recovery system using grammar inference, was developed
to solve this problem. An overview of MARS is illustrated in the
following Figure.
However MARS could only infer metamodels with single-tiered domains,
when it comes to multi-tiered domains which are more widely used in model-driven engineering, due to being
able to represent larger models and enabling users to capture multiple
viewpoints instead of a single one, the performance of MARS is not acceptable
anymore. As a result MARS with extensions is presented to solve
this problem and infer multi-tiered domain models (i.e., ESML models).
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