Abstract. The assembly of components that can handle continuously changing data results in programs that are more interactive. Unfortunately, the code that glues together such components is often difficult to write because it is exposed to many complicated event-handling details. This paper introduces the SuperGlue language where components are assembled by connecting their signals, which declaratively represent state as time-varying values. To support the construction of interactive programs that require an unbounded number of signal connections, signals in SuperGlue are scaled with object-oriented abstractions. With Super-Glue’s combination of signals and objects, programmers can build large interactive programs with substantially less glue code when compared to conventional approaches. For example, the SuperGlue implementation of an email client is around half the size of an equivalent Java implementation. 1

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 dataflow 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. Categories and Subject Descriptors D.3.2 [Programming Languages]: Language Classifications—applicative (functional) languages, data-flow languages, specialized application languages General Terms Languages Keywords dependent types, domain-specific languages, DSELs, FRP, functional programming, reactive programming, synchronous data-flow

functional programming with dataflow evaluation, making it possible to write interactive programs in a declarative style. An frp language creates a dynamic graph of data dependencies and reacts to changes by propagating updates through the graph. In a transparent frp language, the primitive operators are implicitly lifted, so they construct graph nodes when they are applied to time-varying values. This model has some attractive properties, but it tends to produce a large graph that is costly to maintain. In this paper, we develop a transformation we call lowering, which improves performance by reducing the size of the graph. We present a static analysis that guides the sound application of this optimization, and we present benchmark results that demonstrate dramatic improvements in both speed and memory usage for real programs.

Abstract. Functional reactive programming integrates dynamic dataflow with functional programming to offer an elegant and powerful model for expressing computations over time-varying values. Developing realistic applications, however, requires access to libraries, such as those for GUIs, that are written in mainstream object-oriented languages. Previous work has developed functional reactive interfaces for GUI toolkits but has not provided an account of the principles underlying the implementation strategy. In this paper, we investigate this problem by studying the adaptation of the objectoriented toolkit MrEd to the functional reactive language FrTime. The heart of this problem is how to communicate state changes between the application and the toolkit’s widget objects. After presenting a basic strategy for adaptation, we discuss abstraction techniques based on mixins and macros that allow us to adapt numerous properties in many widget classes with minimal code duplication. This results in a wrapper for the entire MrEd toolkit in only a few hundred lines of code. We also briefly discuss a spreadsheet developed with the resulting toolkit. 1

{ cce, matthias} @ ccs.neu.edu For the past five years, the University of Oklahoma has used the ACL2 theorem prover for a year-long sequence on software engineering. The goal of the course is to introduce students to functional programming with “Applicative Common Lisp ” (ACL) and to expose them to defect recognition at all levels, including unit testing, randomized testing of conjectures, and formal theorem proving in “a Computational Logic ” (ACL2). Following Page’s example, Northeastern University has experimented with the introduction of ACL2 into the freshman curriculum for the past two years. Northeastern’s goal is to supplement an introductory course on functional program design with a course on logic and theorem proving that integrates the topic with programming projects. This paper reports on our joint project’s progress. On the technical side, the paper presents the Scheme-based integrated development environment, its run-time environment for functional GUI programming, and its support for different forms of testing. On the experience side, the paper summarizes the introduction of these tools into the courses, the reaction of industrial observers of Oklahoma’s software engineering course, and the feedback from a first outreach workshop.

Abstract. This paper presents a semantics of self-adjusting computation and proves that the semantics is correct and consistent. The semantics integrates change propagation with the classic idea of memoization to enable reuse of computations under mutation to memory. During evaluation, reuse of a computation via memoization triggers a change propagation that adjusts the reused computation to reflect the mutated memory. Since the semantics combines memoization and change-propagation, it involves both non-determinism and mutation. Our consistency theorem states that the non-determinism is not harmful: any two evaluations of the same program starting at the same state yield the same result. Our correctness theorem states that mutation is not harmful: self-adjusting programs are consistent with purely functional programming. We formalized the semantics and its meta-theory in the LF logical framework and machine-checked the proofs in Twelf. 1

Side effects are both the essence and bane of imperative programming. The programmer must carefully coordinate actions to manage their side effects upon each other. Such coordination is complex, error-prone, and fragile. Coherent reaction is a new model of change-driven computation that coordinates effects automatically. State changes trigger events called reactions that in turn change other states. A coherent execution order is one in which each reaction executes before any others that are affected by its changes. A coherent order is discovered iteratively by detecting incoherencies as they occur and backtracking their effects. Unlike alternative solutions, much of the power of imperative programming is retained, as is the common sense notion of mutable state. Automatically coordinating actions lets the programmer express what to do, not when to do it. Coherent reactions are embodied in the Coherence language, which is specialized for interactive applications like those common on the desktop and web. The fundamental building block of Coherence is the dynamically typed mutable tree. The fundamental abstraction mechanism is the virtual tree, whose value is lazily computed, and whose behavior is generated by coherent reactions.

Abstract—We describe a denotational model of higher-order functional reactive programming using ultrametric spaces and nonexpansive maps, which provide a natural Cartesian closed generalization of causal stream functions and guarded recursive definitions. We define a type theory corresponding to this semantics and show that it satisfies normalization. Finally, we show how reactive programs written in this language may be implemented efficiently using an imperatively updated dataflow graph, and give a separation logic proof that this low-level implementation is correct with respect to the high-level semantics. I.

We give a denotational model for graphical user interface (GUI) programming using the Cartesian closed category of ultrametric spaces. The ultrametric structure enforces causality restrictions on reactive systems and allows well-founded recursive definitions by a generalization of guardedness. We capture the arbitrariness of user input (e.g., a user gets to decide the stream of clicks she sends to a program) by making use of the fact that the closed subsets of an ultrametric space themselves form an ultrametric space, allowing us to interpret nondeterminism with a “powerspace ” monad. Algebras for the powerspace monad yield a model of intuitionistic linear logic, which we exploit in the definition of a mixed linear/non-linear domain-specific language for writing GUI programs. The non-linear part of the language is used for writing reactive stream-processing functions whilst the linear sublanguage naturally captures the generativity and usage constraints on the various linear objects in GUIs, such as the elements of a DOM or scene graph. We have implemented this DSL as an extension to OCaml, and give examples demonstrating that programs in this style can be short and readable.

Abstract: 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 data-flow constructs. This raises a range of implementation challenges. 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 hybrid signal function networks with dynamic structure. To sidestep some problems of certain previous FRP implementations that are structured using arrows, we suggest working with a notion of composable, multi-input and multi-output signal functions. A clear conceptual distinction is also made between continuous-time and discrete-time signals. We then show how establishing change-related properties of the signal functions in a network allows such networks to be simplified (static optimisation) and can help reducing the amount of computation needed for executing the networks (dynamic optimisation). Interestingly, distinguishing between continuous-time and discrete-time signals allows us to characterise the change-related properties of signal functions more precisely than what we otherwise would have been able to, which is helpful for optimisation.