Real-time FRP

Functional Reactive Programming (FRP) is an approach to reactive programming where systems are structured as networks of functions operating on signals. FRP is based on the synchronous data-flow paradigm and supports both 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.Statically guaranteeing correctness properties of programs is an attractive proposition. This is true in particular for typical application domains for reactive programming such as embedded systems. To that end, many existing reactive languages have type systems or other static checks that guarantee domain-specific properties, such as feedback loops always being well-formed. However, they are limited in their capabilities to support dynamism and higher-order data-flow compared with FRP. Thus, the onus of ensuring such properties of FRP programs has so far been on the programmer as established static techniques do not suffice.In this paper, we show how dependent types allow this concern to be addressed. We present an implementation of FRP embedded in the dependently-typed language Agda, leveraging the type system of the host language to craft a domain-specific (dependent) type system for FRP. The implementation constitutes a discrete, operational semantics of FRP, and as it passes the Agda type, coverage, and termination checks, we know the operational semantics is total, which means our type system is safe.

Functional Reactive Programming (FRP) models reactive systems with events and signals, which have previously been observed to correspond to the "eventually" and "always" modalities of linear temporal logic (LTL). In this paper, we define a constructive variant of LTL with least fixed point and greatest fixed point operators in the spirit of the modal mu-calculus, and give it a proofs-as-programs interpretation as a foundational calculus for reactive programs. Previous work emphasized the propositions-as-types part of the correspondence between LTL and FRP; here we emphasize the proofs-as-programs part by employing structural proof theory. We show that the type system is expressive enough to enforce liveness properties such as the fairness of schedulers and the eventual delivery of results. We illustrate programming in this calculus using (co)iteration operators. We prove type preservation of our operational semantics, which guarantees that our programs are causal. We give also a proof of strong normalization which provides justification that our programs are productive and that they satisfy liveness properties derived from their types.

Graphical user interfaces (GUIs) mediate many of our interactions with computers. Functional Reactive Programming (FRP) is a promising approach to GUI design, providing high-level, declarative, compositional abstractions to describe user interactions and time-dependent computations. We present Elm, a practical FRP language focused on easy creation of responsive GUIs. Elm has two major features: simple declarative support for Asynchronous FRP ; and purely functional graphical layout. Asynchronous FRP allows the programmer to specify when the global ordering of event processing can be violated, and thus enables efficient concurrent execution of FRP programs; long-running computation can be executed asynchronously and not adversely affect the responsiveness of the user interface. Layout in Elm is achieved using a purely functional declarative framework that makes it simple to create and combine text, images, and video into rich multimedia displays. Together, Elm's two major features simplify the complicated task of creating responsive and usable GUIs.

Functional Reactive Programming (FRP) is an approach to the development of reactive systems which provides a pure functional interface, but which may be implemented as an abstraction of an imperative event-driven layer. FRP systems typically provide a model of behaviours (total time-indexed values, implemented as pull systems) and event sources (partial time-indexed values, implemented as push systems). In this paper, we investigate a type system for event-driven FRP programs which provide liveness guarantees, that is every input event is guaranteed to generate an output event. We show that FRP can be implemented on top of a model of sets and relations, and that the isomorphism between event sources and behaviours corresponds to the isomorphism between relations and set-valued functions. We then implement sets and relations using a model of continuations using the usual double-negation CPS transform. The implementation of behaviours as pull systems based on futures, and of event sources as push systems based on the observer pattern, thus arises from first principles. We also discuss a Java implementation of the FRP model.

Processing data at different rates is generally a hard problem in reactive programming. Buffering problems, lags, and concurrency issues often occur. Many of these problems are clock errors , where data at different rates is combined incorrectly. Techniques to avoid clock errors, such as type-level clocks and deterministic scheduling, exist in the field of synchronous programming, but are not implemented in general-purpose languages like Haskell. Rhine is a clock-safe library for synchronous and asynchronous Functional Reactive Programming (FRP). It separates the aspects of clocking, scheduling and resampling from each other, and ensures clock-safety at the type level. Concurrent communication is encapsulated safely. Diverse reactive subsystems can be combined in a coherent, declarative data-flow framework, while correct interoperability of data at different rates is guaranteed by type-level clocks. This provides a general-purpose framework that simplifies multi-rate FRP systems and can be used for game development, media applications, GUIs and embedded systems, through a flexible API with many reusable components.

Despite the potential of quantum computing for drastically accelerating suitable real-time applications, response time analysis is still required to guarantee that quantum programs running on quantum computers satisfy application-specific timing requirements. This paper describes an inaugural project to determine whether a quantum program running on a quantum computer satisfies the timing constraints of a realtime application, that is, is quantum computing punctual and reliable in this time-sensitive application domain? Can this timing guarantee be formally verified? We leverage the existing work on the functional reactive programming (FRP) model to predict the worst-case response time (WCRT) of fault-tolerant classical computing systems since the timing analysis of re-executions for fault recovery plus transient-faults-induced wasted execution times is similar to determining the response time of FRP tasks. Ongoing work shows that accounting for wasted execution times due to errors in quantum computers resulting from quantum decoherence and state fidelity can be treated similarly and develops a mapping from quantum programs to FRP programs for efficient timing analysis.

FRP (functional reactive programming) is a domain- specific sub-language embedded in Haskell. FRP is developed based on the arrow types and suitable for programming reactive systems such as robot systems. An essential higher-order type, namely signal, provides higher levels of abstractions of reactive systems. However, FRP can not be directly applicable to most robot systems since it is implemented on top of a heavy language Haskell. To overcome this limitation, RT-FRP (real-time functional reactive programming) was proposed, but any practical implementation of RT-FRP has not been proposed currently. In this paper, RT-FRP is implemented as a form of C translator. The proposed translator converts RT-FRP programs into C programs. To measure the effectiveness of the RT-FRP translator, some robot control programs are developed, translated, and loaded on top of LEGO MindStorm. According to the experimental result, the reactive logic can be coded more concisely using RT-FRP than C although the size of the binary code is somewhat increased.

Functional Reactive Programming (FRP) provides a method for programming continuous, reactive systems by utilizing signal functions that, abstractly, transform continuous input signals into continuous output signals. These signals may also be streams of events , and indeed, by allowing signal functions themselves to be the values carried by these events (in essence, signals of signal functions), one can conveniently make discrete changes in program behavior by "switching" into and out of these signal functions. This higher-order notion of switching is common among many FRP systems, in particular those based on arrows, such as Yampa. Although convenient, the power of switching is often an overkill and can pose problems for certain types of program optimization (such as causal commutative arrows [14]), as it causes the structure of the program to change dynamically at run-time. Without a notion of just-in-time compilation or related idea, which itself is beset with problems, such optimizations are not possible at compile time. This paper introduces two new ideas that obviate, in a predominance of cases, the need for switching. The first is a non-interference law for arrows with choice that allows an arrowized FRP program to dynamically alter its own structure (within statically limited bounds) as well as abandon unused streams. The other idea is a notion of a settable signal function that allows a signal function to capture its present state and later be restarted from some previous state. With these two features, canonical uses of higher-order switchers can be replaced with a suitable first-order design, thus enabling a broader range of static optimizations.

Functional reactive programming (FRP) is a paradigm for programming with signals and events, allowing the user to describe reactive programs on a high level of abstraction. For this to make sense, an FRP language must ensure that all programs are causal, and can be implemented without introducing space leaks and time leaks. To this end, some FRP languages do not give direct access to signals, but just to signal functions. Recently, modal types have been suggested as an alternative approach to ensuring causality in FRP languages in the synchronous case, giving direct access to the signal and event abstractions. This paper presents Simply RaTT , a new modal calculus for reactive programming. Unlike prior calculi, Simply RaTT uses a Fitch-style approach to modal types, which simplifies the type system and makes programs more concise. Echoing a previous result by Krishnaswami for a different language, we devise an operational semantics that safely executes Simply RaTT programs without space leaks. We also identify a source of time leaks present in other modal FRP languages: The unfolding of fixed points in delayed computations. The Fitch-style presentation allows an easy way to rules out these leaks, which appears not to be possible in the more traditional dual context approach.

In this paper we introduce a VR system extension that focuses on the creatio n of interactive, dynamic Virtual Environments. The extension uses the recently developed programming co ncept, Functional Reactive Programming. This paradigm focuses on an explicit and more natural concept of time in th e modeling of dynamics, without sacrificing interactivity. We present an implementation that embeds the Functiona l Reactive Programming concept into a basic Virtual Reality system, VR Juggler.

Many types of interactive applications, including reactive systems implemented in hardware, interactive physics simulations and games, raise particular challenges when it comes to testing and debugging. Reasons include de facto lack of reproducibility and difficulties of automatically generating suitable test data. This paper demonstrates that certain variants of functional reactive programming (FRP) implemented in pure functional languages can mitigate such difficulties by offering referential transparency at the level of whole programs. This opens up for a multi-pronged approach for assisting with testing and debugging that works across platforms, including assertions based on temporal logic, recording and replaying of runs (also from deployed code), and automated random testing using QuickCheck. When combined with extensible forms of FRP that allow for constrained side effects, it allows us to not only validate software simulations but to analyse the effect of faults in reactive systems, confirm the efficacy of fault tolerance mechanisms and perform software- and hardware-in-the-loop testing. The approach has been validated on non-trivial systems implemented in several existing FRP implementations, by means of careful debugging using a tool that allows the test or simulation under scrutiny to be controlled, moving along the execution time line, and pin-pointing of violations of assertions on personal computers as well as external devices.

With the book so far, you’ve read every bit of theory about functional reactive programming (FRP) I’ve thrown at you. You also have a working implementation of an FRP library to play with, so you might be wondering: What else is there?

Agent-based modeling (ABM) is a powerful tool for the study of complex systems; but agent-based models are notoriously difficult to create, modify, and reason about, especially in contrast to system dynamics models. We argue that these difficulties are strongly related to the choice of specification language, and that they can be mitigated by using functional reactive programming (FRP), a paradigm for describing dynamic systems. We describe Frabjous, a new language for agent-based modeling based on FRP, and discuss its software engineering benefits and their broader implications for language choice in ABM.

Feasibility interval for the transactional event handlers of P-FRP

Dataflow execution models are used to build highly scalable parallel systems. A programming model that targets parallel dataflow execution must answer the following question: How can parallelism between two dependent nodes in a dataflow graph be exploited? This is difficult when the dataflow language or programming model is implemented by a monad, as is common in the functional community, since expressing dependence between nodes by a monadic bind suggests sequential execution. Even in monadic constructs that explicitly separate state from computation, problems arise due to the need to reason about opaquely defined state. Specifically, when abstractions of the chosen programming model do not enable adequate reasoning about state, it is difficult to detect parallelism between composed stateful computations. In this paper, we propose a programming model that enables the composition of stateful computations and still exposes opportunities for parallelization. We also introduce smap, a higher-order function that can exploit parallelism in stateful computations. We present an implementation of our programming model and smap in Haskell and show that basic concepts from functional reactive programming can be built on top of our programming model with little effort. We compare these implementations to a state-of-the-art approach using monad-par and LVars to expose parallelism explicitly and reach the same level of performance, showing that our programming model successfully extracts parallelism that is present in an algorithm. Further evaluation shows that smap is expressive enough to implement parallel reductions and our programming model resolves short-comings of the stream-based programming model for current state-of-the-art big data processing systems.