The SugarCubes tool box: a reactive Java framework

Boussinot, Frédéric; Susini, Jean-Ferdy

doi:10.1002/(sici)1097-024x(19981210)28:14<1531::aid-spe218>3.0.co;2-u

Cited by 32 publications

(43 citation statements)

References 2 publications

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“…Other related work includes SugarCubes [4], which shares the same concurrency model as ReactiveML but which uses Java as the base language. It allows the creation of reactive machines, the equivalent of our reactive domains, anywhere in the program, but does not offer many ways to communicate and synchronize between machines.…”

Section: Related Workmentioning

confidence: 99%

Time refinement in a functional synchronous language

Mandel

Pasteur²,

Pouzet

2015

Science of Computer Programming

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Concurrent and reactive systems often exhibit multiple time scales. For instance, in a discrete simulation, the scale at which agents communicate might be very different from the scale used to model the internals of each agent.We propose an extension of the synchronous model of concurrency, called reactive domains, to simplify the programming of such systems. Reactive domains allow the creation of local time scales and enable refinement, that is, the replacement of an approximation of a system with a more detailed version without changing its behavior as observed by the rest of the program.Our work is applied to the ReactiveML language, which extends ML with synchronous language constructs. We present an operational semantics for the extended language and a type system that ensures the soundness of programs.

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Section: Related Workmentioning

confidence: 99%

Time refinement in a functional synchronous language

Mandel

Pasteur²,

Pouzet

2015

Science of Computer Programming

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“…SugarCubes [12] and ReactiveML [39] allow reactive programming (in Java and OCAML, respectively) by relying not on operating system and runtime support, as our approach does, but rather on causality analysis and a custom interpreter/compiler. Both systems, however, track dependencies between functional units, through the use of specific language constructs, such as events, and explicit commands for generating and waiting for events.…”

Section: Related Workmentioning

confidence: 99%

Reactive Imperative Programming with Dataflow Constraints

Demetrescu

Finocchi

Ribichini

2014

ACM Trans. Program. Lang. Syst.

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Dataflow languages provide natural support for specifying constraints between objects in dynamic applications, where programs need to react efficiently to changes of their environment. Researchers have long investigated how to take advantage of dataflow constraints by embedding them into procedural languages. Previous mixed imperative/dataflow systems, however, require syntactic extensions or libraries of ad hoc data types for binding the imperative program to the dataflow solver. In this paper we propose a novel approach that smoothly combines the two paradigms without placing undue burden on the programmer.In our framework, programmers can define ordinary statements of the imperative host language that enforce constraints between objects stored in special memory locations designated as "reactive". Differently from previous approaches, reactive objects can be of any legal type in the host language, including primitive data types, pointers, arrays, and structures. Statements defining constraints are automatically re-executed every time their input memory locations change, letting a program behave like a spreadsheet where the values of some variables depend upon the values of other variables. The constraint solving mechanism is handled transparently by altering the semantics of elementary operations of the host language for reading and modifying objects. We provide a formal semantics and describe a concrete embodiment of our technique into C/C++, showing how to implement it efficiently in conventional platforms using off-the-shelf compilers. We discuss common coding idioms and relevant applications to reactive scenarios, including incremental computation, observer design pattern, and data structure repair. The performance of our implementation is compared to ad hoc problem-specific change propagation algorithms, as well as to language-centric apPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. OOPSLA'11, October 22-27, 2011, Portland, Oregon, USA. Copyright c 2011 proaches such as self-adjusting computation and subject/observer communication mechanisms, showing that the proposed approach is efficient in practice.

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“…Argos [Maraninchi 1991], Statecharts [Harel 1987], SyncCharts [André 1996], Argonaute [Maraninchi 1990], Polis [Balarin 1997], Polychrony ], Scade [Dormoy 2008], Simulink/Matlab ]; Language Extensions. ECL (C) 4 [Lavagno and Sentovich 1999], Jester (Java) [Antonotti et al 2000], Reactive-C (C) [Boussinot 1991], Real-time Concurrent C (C) [Gehani and Ramamritham 1991], RTC++ (C++) [Ishikawa et al 1992], Scoop (Eiffel) [Compton 2000], SugarCubes (Java) [Boussinot and Susini 1998]; Hardware Description Languages. Lava [Bjesse et al 1998], SystemC [Initiative 2006], Verilog [Thomas and Moorby 2002], VHDL [IEEE standard 1988]; Models and Intermediate Formats.…”

Section: Synchronous Languagesmentioning

confidence: 99%

Synchronous programming in audio processing

Barkati

Jouvelot

2013

ACM Comput. Surv.

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The adequacy of a programming language to a given software project or application domain is often considered a key factor of success in software development and engineering, even though little theoretical or practical information is readily available to help make an informed decision. In this paper, we address a particular version of this issue by comparing the adequacy of general-purpose synchronous programming languages to more domain-specific languages (DSL) in the field of computer music. More precisely, we implemented and tested the same lookup table oscillator example program, one of the most classical algorithms for sound synthesis, using a selection of significant synchronous programming languages, half of which designed as specific music languages -Csound, Pure Data, SuperCollider, ChucK, Faust -and the other half being general synchronous formalisms -Signal, Lustre, Esterel, Lucid Synchrone and C with the OpenMP Stream Extension (Matlab/Octave is used for the initial specification). The advantages of these two approaches are discussed, providing insights to language designers and possibly software developers of both communities regarding programming languages design for the audio domain.

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The SugarCubes tool box: a reactive Java framework

Cited by 32 publications

References 2 publications

Time refinement in a functional synchronous language

Time refinement in a functional synchronous language

Reactive Imperative Programming with Dataflow Constraints

Synchronous programming in audio processing

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