Developing Applications Using Model-Driven Design Environments

Balasubramanian, Krishnakumar; Gokhale, Aniruddha; Karsai, Gábor; Sztipanovits, János; Neema, Sandeep

doi:10.1109/mc.2006.54

Cited by 138 publications

(72 citation statements)

References 4 publications

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“…Behind all these efforts, it underlies the assumption that using development methods that rely on models and tools with code generation capabilities improves the global developer experience when developing applications, which in turn improves their intention to adopt the method, particularly as systems become larger and more complex [16,17]. This assumption has been reliably supported by different studies that show MDD economical benefits and advantages over both MBD approaches and traditional, code-centric, approaches [18,19].…”

Section: Introductionmentioning

confidence: 99%

MDD vs. traditional software development: A practitioner’s subjective perspective

Martínez

Luján-Mora

Meliá

2013

Information and Software Technology

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Abstract.Context: Today practitioners have a myriad of methods from which to choose for the development of software applications. However they lack empirical data that characterize these methods in terms of usefulness, ease of use or compatibility, all of them relevant variables to assess the developer's intention to use them. OBJECTIVE: To compare three methods, each following a different paradigm (Model-Driven, Model-Based and the traditional, code-centric, respectively) with respect to its intention to use by junior software developers while developing the business layer of a Web 2.0 application. METHOD: We have conducted an experiment with 26 graduate students of the University of Alicante. The application developed was a Social Network, which was organized in three different modules. Subjects were asked to use a different method for each one of the three modules, and then answer a questionnaire that gathered their perceptions during its use. RESULTS: The results show that the method that followed the Model-Driven development paradigm is regarded as the most useful, although it is also regarded as the more difficult to use. They also show that junior software developers feel comfortable with the use of models, and are likely to use them if accompanied by a model-driven development environment. CONCLUSIONS: Model-driven development methods seem to show a great potential for adoption. However, further experimentation is needed to be able to generalize the results to a different population, different methods, languages and tools, different domains or different application sizes.

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Section: Introductionmentioning

confidence: 99%

MDD vs. traditional software development: A practitioner’s subjective perspective

Martínez

Luján-Mora

Meliá

2013

Information and Software Technology

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“…The CVM approach shares some common traits with the concept of model-driven engineering (Bettin, 2004;Balasubramanian et al, 2006Balasubramanian et al, , 2004. In contrast to generalpurpose model-driven development, automatic generation of communication services is feasible in CVM for two reasons: First, CVM is restricted to the scope of communication services and does not bear the complexity of generating general-purpose applications.…”

Section: Model-driven Engineeringmentioning

confidence: 99%

“…Costagliola et al provide a framework that allows the user to define a visual language, create graphical models, validate these models and convert the models into strings of another language. The work in Balasubramanian et al (2006) generates code from models using tool suites for specific application domains that were developed using a generic modeling environment. In our work, a generic SE generates control scripts from a CML description of communication logic, with restricted utility to the communication domain.…”

Section: Model-driven Engineeringmentioning

confidence: 99%

CVM – A communication virtual machine

Deng

Sadjadi

Clarke

et al. 2008

Journal of Systems and Software

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The convergence of data, voice, and multimedia communication over digital networks, coupled with continuous improvement in network capacity and reliability has resulted in a proliferation of communication technologies. Unfortunately, despite these new developments, there is no easy way to build new application-specific communication services. The stovepipe approach used today for building new communication services results in rigid technology, limited utility, lengthy and costly development cycle, and difficulty in integration. In this paper, we introduce communication virtual machine (CVM) that supports rapid conception, specification, and automatic realization of new application-specific communication services through a user-centric, model-driven approach. We present the concept, architecture, modeling language, prototypical design, and implementation of CVM in the context of a healthcare application. Published by Elsevier Inc.

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“…Model-based design [4], [5] emphasizes mathematical modeling to design, analyze, verify, and validate dynamic systems. Mathematical models are used to design, simulate, synthesize, and test cyber-physical systems, and are based on system specifications and analysis of the physical context in which the system resides.…”

Section: Introductionmentioning

confidence: 99%

An introductory capstone design course on embedded systems

Jensen

Lee

Seshia

2011

2011 IEEE International Symposium of Circuits and Systems (ISCAS)

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Abstract-We review an introductory course in embedded systems that characterizes embedded systems not by resource constraints, but rather by interactions with the physical world. This course teaches students the basics of models, analysis tools, and design for embedded systems. Traditional undergraduate courses in embedded systems focus on ad-hoc engineering practices and the use of existing modeling techniques, often omitting critical analysis and meta-modeling; we emphasize model-based design of embedded and cyber-physical systems. Students learn how to model the physical world with continuous time differential equations, and how to model computation using logic and discrete models such as state machines. Students evaluate these modeling techniques through the use of meta-modeling, illuminating the interplay of practical design with formal models of systems that incorporate both physical dynamics and computation. Students learn formal techniques to specify and verify desired behavior. A combination of structured labs and design projects solidifies these concepts when applied to the design of embedded and cyber-physical systems with real-time and concurrent behaviors.

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Developing Applications Using Model-Driven Design Environments

Cited by 138 publications

References 4 publications

MDD vs. traditional software development: A practitioner’s subjective perspective

MDD vs. traditional software development: A practitioner’s subjective perspective

CVM – A communication virtual machine

An introductory capstone design course on embedded systems

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