Back to the future: time travel in FRP

Perez, Ivan

doi:10.1145/3122955.3122957

Cited by 11 publications

(5 citation statements)

References 12 publications

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“…Our FRP debugger has been implemented for Yampa, but the same approach can be used with different AFRP variants like Dunai by means of its API-compatible Yampa replacement layer Bearriver. An advantage of using Dunai over Yampa is that the former only has one type for MSFs, which can be parameterised over the time domain (Perez, 2017a), making it more versatile while reducing code duplication in our debugger. Also, Dunai's monads can be used to implement safe debugging facilities, as shown in Section 5.…”

Section: Discussionmentioning

confidence: 99%

Runtime verification and validation of functional reactive systems

Perez¹,

Nilsson²

2020

J. Funct. Prog.

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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.

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Section: Discussionmentioning

confidence: 99%

Runtime verification and validation of functional reactive systems

Perez¹,

Nilsson²

2020

J. Funct. Prog.

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“…a rendering-loop or other system-dependent sources of non-determinism as described by [38]. Also by using FRP we gain all the benefits from it and can use research on testing, debugging and exploring FRP systems [35,38].…”

Section: Discussionmentioning

confidence: 99%

Pure Functional Epidemics

Thaler

Altenkirch

Siebers

2018

Proceedings of the 30th Symposium on Implementation and Application of Functional Languages

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Agent-Based Simulation (ABS) is a methodology in which a system is simulated in a bottom-up approach by modelling the micro interactions of its constituting parts, called agents, out of which the global system behaviour emerges. So far mainly object-oriented techniques and languages have been used in ABS. Using the SIR model of epidemiology, which simulates the spreading of an infectious disease through a population, we demonstrate how to use pure Functional Reactive Programming to implement ABS. With our approach we can guarantee the reproducibility of the simulation at compile time and rule out specific classes of run-time bugs, something that is not possible with traditional object-oriented languages. Also, we found that the representation in a purely functional format is conceptually quite elegant and opens the way to formally reason about ABS.

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“…Introducing an omissive fault would require a notion of asynchronicity, which can be incorporated into MSFs in multiple ways, the simplest of which would be make outputs optional with Maybe. Different ways of introducing asynchronicity in MSFs have been studied in Perez (2017) and Bärenz & Perez (2018).…”

Section: Injecting Faultsmentioning

confidence: 99%

“…The essence of these languages can be captured via causal stream functions and some forms of functional reactive programming (FRP) (Elliott & Hudak, 1997;Nilsson et al, 2002;Courtney et al, 2003). While FRP has traditionally been applied to domains like interactive programming and games, abstractions like monadic stream functions (MSFs) (Perez et al, 2016;Perez, 2017;Bärenz & Perez, 2018) help bridge the gap between discrete-time causal stream programming and continuous-time FRP.…”

Section: Introductionmentioning

confidence: 99%

“…We later describe basic ideas from the field of fault tolerance, together with an example that illustrates the problems we seek to address. For further details, see earlier papers on FRP (Elliott & Hudak, 1997;Nilsson et al, 2002;Courtney et al, 2003) and MSFs (Perez et al, 2016;Perez, 2017;Bärenz & Perez, 2018). This presentation draws heavily from the summaries in Perez & Nilsson, (2017) and Courtney et al (2003).…”

Section: Introductionmentioning

confidence: 99%

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Fault-tolerant functional reactive programming (extended version)

Perez¹,

Goodloe²

2020

J. Funct. Prog.

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Highly critical application domains, like medicine and aerospace, require the use of strict design, implementation, and validation techniques. Functional languages have been used in these domains to develop synchronous dataflow programming languages for reactive systems. Causal stream functions and functional reactive programming (FRP) capture the essence of those languages in a way that is both elegant and robust. To guarantee that critical systems can operate under high stress over long periods of time, these applications require clear specifications of possible faults and hazards, and how they are being handled. Modeling failure is straightforward in functional languages, and many functional reactive abstractions incorporate support for failure or termination. However, handling unknown types of faults, and incorporating fault tolerance into FRP, requires a different construction and remains an open problem. This work demonstrates how to extend an existing functional reactive framework with fault tolerance features. At value level, we tag faulty signals with reliability and probability information and use random testing to inject faults and validate system properties encoded in temporal logic. At type level, we tag components with the kinds of faults they may exhibit and use type-level programming to obtain compile-time guarantees of key aspects of fault tolerance. Our approach is powerful enough to be used in systems with realistic complexity, and flexible enough to be used to guide system analysis and design, validate system properties in the presence of faults, perform runtime monitoring, and study the effects of different fault tolerance mechanisms.

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Back to the future: time travel in FRP

Cited by 11 publications

References 12 publications

Runtime verification and validation of functional reactive systems

Runtime verification and validation of functional reactive systems

Pure Functional Epidemics

Fault-tolerant functional reactive programming (extended version)

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