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An adaptive middleware design to support the dynamic interpretation of domain-specific models Karl A. Morris a,⇑ , Mark Allison b , Fábio M. Costa c , Jinpeng Wei d , Peter J. Clarke d a Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA b School of Computer Science, Engineering, and Physics, University of Michigan-Flint, Flint, MI 48502, USA c Instituto de Informática, Universidade Federal de Goiás, CEP 74690-815, Goiânia, GO, Brazil d School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA a r t i c l e i n f o  Article history: Received 7 November 2013 Received in revised form 7 February 2015 Accepted 9 February 2015 Available online 15 February 2015 Keywords: Models at runtime Adaptable middleware Domain independen ce Domain specific classifier a b s t r a c t Context:  As the use of Domain-Specific Modeling Languages (DSMLs) continues to gain popularity, we ha ve de ve lop ed ne w wa ys to exec ute DSML mo de ls. Themost pop ula r ap pro achis to ex ecute cod e re sul t- ing from a model-to-code transformation. An alternative approach is to directly execute these models using a semantic-rich execution engine – Domain-Specific Virtual Machine (DSVM). The DSVM includes a middleware layer responsible for the delivery of services in a given domain. Objective:  We will investigate an approach that performs the dynamic combination of constructs in the middleware layer of DSVMs to support the delivery of domain-specific services. This middleware should provide: (a) a model of execution (MoE) that dynamically integrates decoupled domain-specific knowl- edge (DSK) for service delivery, (b) runtime adaptability based on context and available resources, and (c) the same level of operational assurance as any DSVM middleware. Method:  Our approach will involve (1) defining a framework that supports the dynamic combination of MoE and DSK and (2) demonstrating the applicability of our framework in the DSVM middleware for user-centric communication. We will measure the overhead of our approach and provide a cost-benefit analysis factoring in its runtime adaptability using appropriate experimentation. Results:  Our experiments show that combining the DSK and MoE for a DSVM middleware allow us to realize efficient specialization while maintaining the required operability. We also show that the over- head introduced by adaptation is not necessarily deleterious to overall performance in a domain as it may result in more efficient operation selection. Conclusion:  The app roach defi ned for the DSVM mid dlew are allo ws for gre ater flex ibili ty in serv ice del iv- er y wh ile re ducin g thecomp lex ity of app lic ati on de ve lop me nt for theuser. These be ne fits are ac hie ve d at the expense of increased execution times, however this increase may be negligible depending on the domain.  2015 Elsevier B.V. All rights reserved. 1. Introduction Mo del Dri ven Soft war e Dev elop men t (MDSD ) has beco me a widely use d par adig m in the area of soft war e eng ine erin g wit h its gro wth increa sing in rece nt yea rs  [20,43]. As a result of the growth of MDSD there has also been much interest in Domain- Specific Modeling Languag es (DSMLs), particu larly, the graphical ver sion of DSM Ls  [19,26,27] . Con ven tio nal app roa ches to usin g DSM Ls focus on model tran sfor mat ion utilize d in oth er areas of soft war e enginee rin g, whe re models in one lan gua ge are translat ed into another langu age prior to executio n, e.g., mode ls created in UML are translated into Java  [31,34] . A developing trend in this area is to remove the steps involved in conventional model trans- lation, and to instead execute the models directly. This approach re quire s a semanticall y ric h en vir on me nt wh ich is able to inte rp ret models at this level of abstraction. A class of DSMLs that sup ports mo del executi on using a seman- tically rich execution engine is referred to as  Interpreted Domain- Specific Modeling Languages  (i-DSMLs)  [11]. An i-DSML execution engine is one approch that provides a facility for the direct execu- tion of models by using a 4-layered architecture, where each layer receives and performs operation s on an increasin gly granular view of the model, before passing the transformed version of the model http://dx.doi.org/10.1016/j.infsof.2015.02.003 0950-5849/ 2015 Elsevier B.V. All rights reserved. ⇑ Correspondin g author. E-mail addresses:  karl.morris@tem ple.edu (K.A. Morris),  markalli@umflint.edu (M. Allison),  [email protected] r (F.M. Costa),  weijp@cis.fiu .edu (J. Wei),  clarkep@cis.fiu. edu (P.J. Clarke). Information and Software Technology 62 (2015) 21–41 Contents lists available at  ScienceDirect Information and Software Technology journal homepage:  www.elsevier.com/locate/infsof  

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