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Challenges and directions in formalizing the semantics of modeling languages
Barrett Richard Bryant, Jeffrey G. Gray, Marjan Mernik, Peter Clarke, Robert France, Gabor Karsai, 2011, original scientific article

Abstract: Developing software from models is a growing practice and there exist many model-based tools (e.g., editors, interpreters, debuggers, and simulators) forsupporting model-driven engineering. Even though these tools facilitate theautomation of software engineering tasks and activities, such tools are typically engineered manually. However, many of these tools have a common semantic foundation centered around an underlying modeling language, which would make it possible to automate their development if the modeling language specification were formalized. Even though there has been much work in formalizing programming languages, with many successful tools constructed using such formalisms, there has been little work in formalizing modeling languages for the purpose of automation. This paper discusses possible semantics-based approaches for the formalization of modeling languages and describes how this formalism may be used to automate the construction of modeling tools.
Keywords: model-based tools, modeling language, semantics
Published in DKUM: 06.07.2017; Views: 855; Downloads: 349
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MARS: A Metamodel Recovery System Using Grammar Inference
Faizan Javed, Marjan Mernik, Jeffrey G. Gray, Barrett Richard Bryant, 2008, original scientific article

Abstract: Domain-specific modeling (DSM) assists subject matter experts in describing the essential characteristics of a problem in their domain. When a metamodel is lost, repositories of domain models can become orphaned from their defining metamodel. Within the purview of model-driven engineering, the ability to recover the design knowledge in a repository of legacy models is needed. In this paper we describe MARS, a semi-automatic grammar-centric system that leverages grammar inference techniques to solve the metamodel recovery problem. The paper also contains an applicative case study, as well as experimental results from the recovery of several metamodels in diverse domains.
Keywords: domain-specific languages, metamodeling, recovery systems, reverse engineering, re-ingineering
Published in DKUM: 01.06.2012; Views: 1244; Downloads: 96
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Embedding DSLS into GPLS
Dejan Hrnčič, Marjan Mernik, Barrett Richard Bryant, 2011, original scientific article

Abstract: Embedding of Domain-Specific Languages (DSLs) into General-Purpose Languages (GPLs) is oftenused to express domain-specific problems using the domainćs natural syntax inside GPL programs. It speeds up thedevelopment process, programs are more self-explanatory and repeating tasks are easier to handle. End-users ordomain experts know what the desired language syntax would look like, but do not know how to write a grammar andlanguage processing tools. Grammatical inference can be used for grammar extraction from input examples. Amemetic algorithm for grammatical inference, named MAGIc, was implemented to extract grammar from DSLexamples. In this work MAGIc is extended with embedding the inferred DSL into existing GPL grammar.Additionally, negative examples were also incorporated into the inference process. From the results it can be concludedthat MAGIc is successful for DSL embedding and that the inference process is improved with use of negativeexamples.
Keywords: memetic algorithms, doamin-specific languages, grammatical inference, embedding
Published in DKUM: 01.06.2012; Views: 1299; Downloads: 42
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Is my DSL a modeling or programming language?
Yu Sun, Zekai Demirezen, Marjan Mernik, Jeffrey G. Gray, Barrett Richard Bryant, 2008, published scientific conference contribution

Abstract: It is often difficult to discern the differences between programming and modeling languages. As an example, the term "domain-specific language" has been used almost interchangeably in academia and industry to represent both programming and modeling languages, which has caused subtle misconceptions. The borders between a modeling and programming language are somewhat vague and not defined crisply. This paper discusses the similarities and differences between modeling and programming languages, and offers some suggestions on how to better differentiate such languages. A list of criteria is presented for language classification, but it is suggested that a set of the criteria be used, rather than a single criterion. Several example domain-specific languages are used as case studies to motivate the discussion.
Keywords: domain-specific languages, programming languages, modeling language
Published in DKUM: 31.05.2012; Views: 1316; Downloads: 35
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