Transformation in intentional programming

Aitken, W. E. M.; Dickens, Brian; Kwiatkowski, P.; Moor, Oege de; Richter, Dirk; Simonyi, Charles

doi:10.1109/icsr.1998.685736

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…For example, in MIC, the models (which are the expression of domain-specific constructs, designs) are represented in model databases in a format, which is independent from the concrete syntax used during modeling. Model transformation has a similarly central role in MIC as transformers in IP [59]: the MIC generators are all directly manipulating the content of model databases for visualizing, analyzing, and composing models at different phases of the system development. Both in MIC and IP, efficient technology for defining and implementing transformers is a crucial issue.…”

Section: Intentional Programming (Ip)mentioning

confidence: 99%

Model-integrated development of embedded software

et al. 2003

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The paper describes a model-integrated approach for embedded software development that is based on domain-specific, multiple-view models used in all phases of the development process. Models explicitly represent the embedded software and the environment it operates in, and capture the requirements and the design of the application, simultaneously. Models are descriptive, in the sense that they allow the formal analysis, verification, and validation of the embedded system at design time. Models are also generative, in the sense that they carry enough information for automatically generating embedded systems using the techniques of program generators. Because of the widely varying nature of embedded systems, a single modeling language may not be suitable for all domains; thus, modeling languages are often domain-specific. To decrease the cost of defining and integrating domain-specific modeling languages and corresponding analysis and synthesis tools, the model-integrated approach is applied in a metamodeling architecture, where formal models of domain-specific modeling languages-called metamodels-play a key role in customizing and connecting components of tool chains. This paper discusses the principles and techniques of model-integrated embedded software development in detail, as well as the capabilities of the tools supporting the process. Examples in terms of real systems will be given that illustrate how the model-integrated approach addresses the physical nature, the assurance issues, and the dynamic structure of embedded software.

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Section: Intentional Programming (Ip)mentioning

confidence: 99%

Model-integrated development of embedded software

et al. 2003

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“…Other generative and metaprogramming paradigms, such as intentional programming [1], allow programmers to create code in a higher level of abstraction. They also address the issues related to productivity by making program code more accessible for tools.…”

Section: Related Workmentioning

confidence: 99%

When importless becomes meaningful

Tauber

2014

Proceedings of the Companion Publication of the 2014 ACM SIGPLAN Conference on Systems, Programming, and Applications: Software

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Traditional programming language namespaces evolved from filesystem structures. We describe different scenarios where this rigid code organization becomes a limiting factor. After that, we propose a more flexible code organization using tags. We then illustrate it on Python, including how we can convert existing code structures to the new tag-based one. Finally, we discuss our plans how to extend this work to statically typed languages in the future.

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“…The Garden [31][32][33] and Escalante [26] systems tried to do this for visual languages; the proposed DARPA prototyping language tried to do this at the specification level; and, more recently, the intentional programming efforts at Microsoft [1] try to combine multiple approaches in a single textual framework. These approaches tend to concentrate on different programming dimensions, and generally ignore specifications and design as well as documentation and historical dimensions.…”

Section: Prior Workmentioning

confidence: 99%

Constraining software evolution

Reiss

International Conference on Software Maintenance, 2002. Proceedings.

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MotivationMost developers think of a software system as the code and components that are the end result of the software development process. As code is written, developers gradually ignore the initial stages of development, the specifications and the design of the system, the documentation, the component specifications, and the test cases. This narrow view of software is one of the primary causes of the many problems associated with software and its development [9].We visualize an environment where all the aspects of software development evolve consistently as the system is developed and maintained. As any one of these aspects changes, the environment would ensure that all other aspects are updated accordingly. This would simplify both software development and maintenance as it would guarantee that all aspects were relevant, accurate, and up-todate.Such an environment can be built by defining constraints between the artifacts representing the different software aspects. When an artifact is updated, all the constraints on that artifact are triggered and any related artifacts are checked for consistency. Consistency can then be maintained either automatically or by informing the developer what needs to be done before the change is complete.In this paper we demonstrate that such an environment based on constraints can be built and used effectively for a wide range of software artifacts. Software EvolutionSoftware is not just the source code; instead it is multidimensional [19]. The specifications, design, architecture, test cases, user interfaces, coding conventions, components, constraints, design patterns, system architecture, development history, and documentation are all as much a part of a software system as is the physical code. Furthermore, these other artifacts are sometimes much more valuable than the code itself. Software development and programmer productivity therefore depend on being able to develop, relate, and consistently maintain all these different aspects of the software.Today's software environments provide a wide variety of tools to handle the many of dimensions of software. Environments provide tools for managing, editing, and debugging the source code; tools for developing and experimenting with user interfaces; tools for specifying the design using UML or similar notations; and tools for creating and managing test cases for a system. Research environments have demonstrated tool prototypes for managing design patterns, components, and constraints [3,6,8,16,17,22,24,25,27,29,40]. There are also tools specifically designed to handle software evolution. Most of these tools only deal with the source code and use semantic analysis to either identify code affected by potential changes [2,15,42,47] or that assist in refactoring [5,24,41].These tools, especially those dealing with different aspects of software, are rarely integrated with one another. As a result, software routinely evolves inconsistently along the different dimensions. Typically, developers create an initial design, but, as ...

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Transformation in intentional programming

Cited by 7 publications

References 10 publications

Model-integrated development of embedded software

Model-integrated development of embedded software

When importless becomes meaningful

Constraining software evolution

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