Keeping calm in the face of change Towards optimisation of FRP by reasoning about change

Functional Reactive Programming (FRP) is an approach to reactive programming where systems are structured as networks of functions operating on signals (time-varying values). FRP is based on the synchronous data-flow paradigm and supports both (an approximation to) continuous-time and discrete-time...

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Veröffentlicht in:Higher-Order and Symbolic Computation Jg. 23; H. 2; S. 227 - 271
Hauptverfasser: Sculthorpe, Neil, Nilsson, Henrik
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.06.2010
Springer
Schlagworte:
Applied sciences
Combinatorics. Ordered structures
Computational Intelligence
Computational Mathematics and Numerical Analysis
Computer Science
Computer science; control theory; systems
Exact sciences and technology
Mathematical analysis
Mathematical Logic and Formal Languages
Mathematics
Miscellaneous
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming, optimization and calculus of variations
Numerical methods in optimization and calculus of variations
Order, lattices, ordered algebraic structures
Real functions
Sciences and techniques of general use
Symbolic and Algebraic Manipulation
Theoretical computing
Hybrid systems
Change propagation
Synchronous data-flow
Functional reactive programming
Domain-specific languages
Approximation
Optimization method
Continuous time
Continuous function
Discrete system
Symbolic computation
Implementation
Temporal logic
Numerical analysis
Reasoning
Denotational semantics
Discrete time
Variational calculus
Functional programming
Mathematical programming
ISSN:1388-3690, 1573-0557
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Zusammenfassung:Functional Reactive Programming (FRP) is an approach to reactive programming where systems are structured as networks of functions operating on signals (time-varying values). FRP is based on the synchronous data-flow paradigm and supports both (an approximation to) continuous-time and discrete-time signals (hybrid systems). What sets FRP apart from most other languages for similar applications is its support for systems with dynamic structure and for higher-order reactive constructs. This paper contributes towards advancing the state of the art of FRP implementation by studying the notion of signal change and change propagation in a setting of structurally dynamic networks of n -ary signal functions operating on mixed continuous-time and discrete-time signals. We first define an ideal denotational semantics (time is truly continuous) for this kind of FRP, along with temporal properties, expressed in temporal logic, of signals and signal functions pertaining to change and change propagation. Using this framework, we then show how to reason about change; specifically, we identify and justify a number of possible optimisations, such as avoiding recomputation of unchanging values. Note that due to structural dynamism, and the fact that the output of a signal function may change because time is passing even if the input is unchanging, the problem is significantly more complex than standard change propagation in networks with static structure.
ISSN:1388-3690
1573-0557
DOI:10.1007/s10990-011-9068-x