32,666 research outputs found

    Conceptual design of sound, custom composition languages

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    Service composition, web mashups, and business process modeling are based on the composition and reuse of existing functionalities, user interfaces, or tasks. Composition tools typically come with their own, purposely built composition languages, based on composition techniques like data flow or control flow, and only with minor distinguishing features-besides the different syntax. Yet, all these composition languages are developed from scratch, without reference specifications (e.g., XML schemas), and by reasoning in terms of low-level language constructs. That is, there is neither reuse nor design support in the development of custom composition languages. We propose a conceptual design technique for the construction of custom composition languages that is based on a generic composition reference model and that fosters reuse. The approach is based on the abstraction of common composition techniques into high-level language features, a set of reference specifications for each feature, and the assembling of features into custom languages by guaranteeing their soundness. We specifically focus on mashup languages

    Free composition instead of language dictatorship

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    Historically, programming languages have been—benevolent—dictators: reducing all possible semantics to specific ones offered by a few built-in language constructs. Over the years, some programming languages have freed the programmers from the restrictions to use only built-in libraries, built-in data types, and builtin type-checking rules. Even though—arguably—such freedom could lead to anarchy, or people shooting themselves in the foot, the contrary tends to be the case: a language that does not allow for extensibility is depriving software engineers of the ability to construct proper abstractions and to structure software in the most optimal way. Therefore the software becomes less structured and maintainable than would be possible if the software engineer could express the behavior of the program with the most appropriate abstractions. The idea proposed by this paper is to move composition from built-in language constructs to programmable, first-class abstractions in a language. We discuss several prototypes of the Co-op language, which show that it is possible, with a relatively simple model, to express a wide range of compositions as first-class concepts

    Liberating Composition from Language Dictatorship

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    Historically, programming languages have been—although benevolent—dictators: fixing a lot of semantics into built-in language constructs. Over the years, (some) programming languages have freed the programmers from restrictions to use only built-in libraries, built-in data types, or built-in type checking rules. Even though, arguably, such freedom could lead to anarchy, or people shooting themselves in the foot, the contrary tends to be the case: a language that does not allow for extensibility, is depriving software engineers from the ability to construct proper abstractions and to structure software in the most optimal way. Instead, the software becomes less structured and maintainable than would be possible if the software engineer could express the behavior of the program with the most appropriate abstractions. The new idea proposed by this paper is to move composition from built-in language constructs to programmable, first-class abstractions in the language. As an emerging result, we present the Co-op concept of a language, which shows that it is possible with a relatively simple model to express a wide range of compositions as first-class concepts

    CSP design model and tool support

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    The CSP paradigm is known as a powerful concept for designing and analysing the architectural and behavioural parts of concurrent software. Although the theory of CSP is useful for mathematicians, the programming language occam has been derived from CSP that is useful for any engineering practice. Nowadays, the concept of occam/CSP can be used for almost every object-oriented programming language. This paper describes a tree-based description model and prototype tool that elevates the use of occam/CSP concepts at the design level and performs code generation to Java, C, C++, and machine-readable CSP for the level of implementation. The tree-based description model can be used to browse through the generated source code. The tool is a kind of browser that is able to assist modern workbenches (like Borland Builder, Microsoft Visual C++ and 20-SIM) with coding concurrency. The tool will guide the user through the design trajectory using support messages and several semantic and syntax rule checks. The machine-readable CSP can be read by FDR, enabling more advanced analysis on the design. Early experiments with the prototype tool show that the browser concept, combined with the tree-based description model, enables a user-friendly way to create a design using the CSP concepts and benefits. The design tool is available from our URL, http://www.rt.el.utwente.nl/javapp

    Conceptual development of custom, domain-specific mashup platforms

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    Despite the common claim by mashup platforms that they enable end-users to develop their own software, in practice end-users still don't develop their own mashups, as the highly technical or inexistent user bases of today's mashup platforms testify. The key shortcoming of current platforms is their general-purpose nature, that privileges expressive power over intuitiveness. In our prior work, we have demonstrated that a domainspecific mashup approach, which privileges intuitiveness over expressive power, has much more potential to enable end-user development (EUD). The problem is that developing mashup platforms - domain-specific or not - is complex and time consuming. In addition, domain-specific mashup platforms by their very nature target only a small user basis, that is, the experts of the target domain, which makes their development not sustainable if it is not adequately supported and automated. With this article, we aim to make the development of custom, domain-specific mashup platforms costeffective. We describe a mashup tool development kit (MDK) that is able to automatically generate a mashup platform (comprising custom mashup and component description languages and design-time and runtime environments) from a conceptual design and to provision it as a service. We equip the kit with a dedicated development methodology and demonstrate the applicability and viability of the approach with the help of two case studies. © 2014 ACM

    Herding cats: observing live coding in the wild

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    After a momentous decade of live coding activities, this paper seeks to explore the practice with the aim of situating it in the history of contemporary arts and music. The article introduces several key points of investigation in live coding research and discusses some examples of how live coding practitioners engage with these points in their system design and performances. In the light of the extremely diverse manifestations of live coding activities, the problem of defining the practice is discussed, and the question raised whether live coding will actually be necessary as an independent category

    Semantic Component Composition

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    Building complex software systems necessitates the use of component-based architectures. In theory, of the set of components needed for a design, only some small portion of them are "custom"; the rest are reused or refactored existing pieces of software. Unfortunately, this is an idealized situation. Just because two components should work together does not mean that they will work together. The "glue" that holds components together is not just technology. The contracts that bind complex systems together implicitly define more than their explicit type. These "conceptual contracts" describe essential aspects of extra-system semantics: e.g., object models, type systems, data representation, interface action semantics, legal and contractual obligations, and more. Designers and developers spend inordinate amounts of time technologically duct-taping systems to fulfill these conceptual contracts because system-wide semantics have not been rigorously characterized or codified. This paper describes a formal characterization of the problem and discusses an initial implementation of the resulting theoretical system.Comment: 9 pages, submitted to GCSE/SAIG '0

    Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

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    To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable
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