Monad Transformers Research Articles

Lightweight monadic regions

We present Haskell libraries that statically ensure the safe use of resources such as file handles. We statically prevent accessing an already closed handle or forgetting to close it. The libraries can be trivially extended to other resources such as database connections and graphic contexts. Because file handles and similar resources are scarce, we want to not just assure their safe use but further deallocate them soon after they are no longer needed. Relying on Fluet and Morrisett's [4] calculus of nested regions, we contribute a novel, improved, and extended implementation of the calculus in Haskell, with file handles as resources. Our library supports region polymorphism and implicit region subtyping, along with higher-order functions, mutable state, recursion, and run-time exceptions. A program may allocate arbitrarily many resources and dispose of them in any order, not necessarily LIFO. Region annotations are part of an expression's inferred type. Our new Haskell encoding of monadic regions as monad transformers needs no witness terms. It assures timely deallocation even when resources have markedly different lifetimes and the identity of the longest-living resource is determined only dynamically. For contrast, we also implement a Haskell library for manual resource management, where deallocation is explicit and safety is assured by a form of linear types. We implement the linear typing in Haskell with the help of phantom types and a parameterized monad to statically track the type-state of resources.

Making monads first-class with template haskell

Monads as an organizing principle for programming and semantics are notoriously difficult to grasp, yet they are a central and powerful abstraction in Haskell. This paper introduces a domain-specific language, MonadLab, that simplifies the construction of monads, and describes its implementation in Template Haskell. MonadLab makes monad construction truly first class, meaning that arcane theoretical issues with respect to monad transformers are completely hidden from the programmer. The motivation behind the design of MonadLab is to make monadic programming in Haskell simpler while providing a tool for non-Haskell experts that will assist them in understanding this powerful abstraction.

A novel formal approach to program slicing

Program slicing is a well-known program analysis technique that extracts the elements of a program related to a particular computation. The current slicing methods, however, are singular (mainly based on a program or system dependence graph), and lack good reusability and flexibility. In this paper, we present a novel formal method for program slicing, modular monadic program slicing, which abstracts the computation of program slicing as a slice monad transformer, and applies it to semantic descriptions of the program analyzed in a modular way, forming the corresponding monadic slicing algorithms. The modular abstraction mechanism allows our slicing method to possess excellent modularity and language-flexibility properties. We also give the related axioms of our slice monad transformer, the proof of the correctness and the implementation of monadic slicing algorithms. We reveal the relations of our algorithms and graph-reachable slicing algorithms.

Combining algebraic effects with continuations

We consider the natural combinations of algebraic computational effects such as side-effects, exceptions, interactive input/output, and nondeterminism with continuations. Continuations are not an algebraic effect, but previously developed combinations of algebraic effects given by sum and tensor extend, with effort, to include commonly used combinations of the various algebraic effects with continuations. Continuations also give rise to a third sort of combination, that given by applying the continuations monad transformer to an algebraic effect. We investigate the extent to which sum and tensor extend from algebraic effects to arbitrary monads, and the extent to which Felleisen et al.’s C operator extends from continuations to its combination with algebraic effects. To do all this, we use Dubuc’s characterisation of strong monads in terms of enriched large Lawvere theories.

Programming monads operationally with Unimo

Monads are widely used in Haskell for modeling computational effects, but defining monads remains a daunting challenge. Since every part of a monad's definition depends on its computational effects, programmers cannot leverage the common behavior of all monads easily and thus must build from scratch each monad that models a new computational effect.I propose the Unimo framework which allows programmers to define monads and monad transformers in a modular manner. Unimo contains a heavily parameterized observer function which enforces the monad laws, and programmers define a monad by invoking the observer function with arguments that specify the computational effects of the monad. Since Unimo provides the common behavior of all monads in a reusable form, programmers no longer need to rebuild the semantic boilerplate for each monad and can instead focus on the more interesting and rewarding task of modeling the desired computational effects.

A monadic program slicer

Program slicing is an important decomposition technique. It has been widely used in many software activities, such as software analyzing, understanding, debugging, testing, and maintenance. The current slicing methods and tools, however, are monolithic, and mainly based on program or system dependence graph. This paper presents a novel formal tool for program slicing. It abstracts the computation of program slicing as a language-independent slice monad transformer, which can be applied to the semantic descriptions of the program in a modular way, forming the corresponding slicing algorithms. Such algorithms allow program slices to be computed directly on abstract syntax, with no need to explicitly construct intermediate structures such as dependence graphs or to record an execution history. It has reusability and language-flexibility properties in comparison with the current program slicing methods/tools.

Combining effects: Sum and tensor

We seek a unified account of modularity for computational effects. We begin by reformulating Moggi's monadic paradigm for modelling computational effects using the notion of enriched Lawvere theory, together with its relationship with strong monads; this emphasises the importance of the operations that produce the effects. Effects qua theories are then combined by appropriate bifunctors on the category of theories. We give a theory for the sum of computational effects, which in particular yields Moggi's exceptions monad transformer and an interactive input/output monad transformer. We further give a theory of the commutative combination of effects, their tensor, which yields Moggi's side-effects monad transformer. Finally, we give a theory of operation transformers, for redefining operations when adding new effects; we derive explicit forms for the operation transformers associated to the above monad transformers.

Backtracking, interleaving, and terminating monad transformers

We design and implement a library for adding backtracking computations to any Haskell monad. Inspired by logic programming, our library provides, in addition to the operations required by the MonadPlus interface, constructs for fair disjunctions, fair conjunctions, conditionals, pruning, and an expressive top-level interface. Implementing these additional constructs is easy in models of backtracking based on streams, but not known to be possible in continuation-based models. We show that all these additional constructs can be generically and monadically realized using a single primitive msplit . We present two implementations of the library: one using success and failure continuations; and the other using control operators for manipulating delimited continuations.

Composing monads using coproducts

Monads are a useful abstraction of computation, as they model diverse computational effects such as stateful computations, exceptions and I/O in a uniform manner. Their potential to provide both a modular semantics and a modular programming style was soon recognised. However, in general, monads proved difficult to compose and so research focused on special mechanisms for their composition such as distributive monads and monad transformers.We present a new approach to this problem which is general in that nearly all monads compose, mathematically elegant in using the standard categorical tools underpinning monads and computationally expressive in supporting a canonical recursion operator. In a nutshell, we propose that two monads should be composed by taking their coproduct . Although abstractly this is a simple idea, the actual construction of the coproduct of two monads is non-trivial. We outline this construction, show how to implement the coproduct within Haskell and demonstrate its usage with a few examples. We also discuss its relationship with other ways of combining monads, in particular distributive laws for monads and monad transformers.

Monads for incremental computing

This paper presents a monadic approach to incremental computation, suitable for purely functional languages such as Haskell. A program that uses incremental computation is able to perform an incremental amount of computation to accommodate for changes in input data. Recently, Acar, Blelloch and Harper presented a small Standard ML library that supports efficient, high-level incremental computations [1]. Here, we present a monadic variant of that library, written in Haskell extended with first-class references. By using monads, not only are we able to provide a purely functional interface to the library, the types also enforce "correct usage" without having to resort to any type-system extension. We also find optimization opportunities based on standard monadic combinators.This is an exercise in putting to work monad transformers with environments, references, and continuations.

Specification of Logic Programming Languages from Reusable Semantic Building Blocks

We present a Language Prototyping System that facilitates the modular development of interpreters from independent semantic building blocks. The abstract syntax is modelled as the fixpoint of a pattern functor which can be obtained as the sum of functors. For each functor we define an algebra whose carrier is the computational structure. This structure is obtained as the composition of several monad transformers applied to a base monad, where each monad transformer adds a new notion of computation. When the abstract syntax is composed from mutually recursive categories, we use many-sorted algebras. With this approach, the prototype interpreters are automatically obtained as a catamorphism over the defined algebras.As an example, in this paper, we independently specify an arithmetic evaluator and a simple logic programming language and combine both specifications to obtain a logic programming language with arithmetic capabilities.

LPS: A Language Prototyping System Using Modular Monadic Semantics

This paper describes LPS, a Language Prototyping System that facilitates the modular development of interpreters from semantic building blocks. The system is based on the integration of ideas from Modular Monadic Semantics and Generic Programming.To define a new programming language, the abstract syntax is described as the fixpoint of non-recursive pattern functors. For each functor an algebra is defined whose carrier is the computational monad obtained from the application of several monad transformers to a base monad. The interpreter is automatically generated by a catamorphism or, in some special cases, a monadic catamorphism.The system has been implemented as a domain-specific language embedded in Haskell and we have also implemented an interactive framework for language testing.

PROLOG'S CONTROL CONSTRUCTS IN A FUNCTIONAL SETTING — AXIOMS AND IMPLEMENTATION

The purpose of this article is twofold. First, we show that Prolog's control constructs can be smoothly integrated into a functional language like Haskell. The resulting 'language', termed embedded Prolog, incorporates many of the features prescribed by the Prolog ISO standard: control constructs including the cut, all solution collecting functions, and error handling facilities. Embedded Prolog lacks some concepts such as logical variables but it inherits all of Haskell's strengths, eg static polymorphic typing, higher order functions etc. Technically, the integration is achieved using monads and monad transformers. One of the main innovations is the definition of a backtracking monad transformer, which allows us to combine backtracking with exception handling and interaction. Second, we work towards an axiomatization of the operations, through which the computational features are accessed. Equations are used to lay down the meaning of the various operations and their interrelations enabling the programmer to reason about programs in a simple calculational style. The axiomatization is applied to show that each finite computation has a simple canonical form.

Deriving backtracking monad transformers

In a paper about pretty printing J. Hughes introduced two fundamental techniques for deriving programs from their specification, where a specification consists of a signature and properties that the operations of the signature are required to satisfy. Briefly, the first technique, the term implementation, represents the operations by terms and works by defining a mapping from operations to observations --- this mapping can be seen as defining a simple interpreter. The second, the context-passing implementation, represents operations as functions from their calling context to observations. We apply both techniques to derive a backtracking monad transformer that adds backtracking to an arbitrary monad. In addition to the usual backtracking operations --- failure and nondeterministic choice --- the prolog cut and an operation for delimiting the effect of a cut are supported.

Foundations of Modular SOS

A novel form of labelled transition system is proposed, where<br />the labels are the arrows of a category, and adjacent labels in computations<br /> are required to be composable. Such transition systems provide the<br />foundations for modular SOS descriptions of programming languages.<br />Three fundamental ways of transforming label categories, analogous to<br />monad transformers, are provided, and it is shown that their applications<br />preserve computations in modular SOS. The approach is illustrated with<br />fragments taken from a modular SOS for ML concurrency primitives.

A poor man's concurrency monad

Without adding any primitives to the language, we define a concurrency monad transformer in Haskell. This allows us to add a limited form of concurrency to any existing monad. The atomic actions of the new monad are lifted actions of the underlying monad. Some extra operations, such as fork, to initiate new processes, are provided. We discuss the implementation, and use some examples to illustrate the usefulness of this construction.

Semantics, Modularity, and Rewriting Logic

A complete formal semantic description of a practical programming language (such as Java) is likely to be a lengthy document, regardless of which semantic framework is being used. Good modularity of the description is important to the person(s) developing it, to facilitate reuse, change, and extension. Unfortunately, the conventional versions<br />of the major semantic frameworks have rather poor modularity.<br /> In this paper, we first recall some approaches that improve the modularity of denotational semantics, namely action semantics, modular monadic semantics, and a hybrid framework that combines these: modular monadic action semantics. We then address the issue of modularity in operational semantics, which appears to have received comparatively little attention so far, and report on some preliminary investigations of how one might achieve the same kind of modularity in structural operational semantics as the use of monad transformers<br />can provide in denotational semantics|this is the main technical contribution of the paper. Finally, we briefly consider the representation of structural operational semantics in rewriting logic, and speculate on the possibility of using it to interpret programs in the described language. Providing powerful meta-tools for such semantics-based interpretation<br />is an interesting potential application of rewriting logic;<br />good modularity of the semantic descriptions may be crucial for the practicality of using the tools.<br />Much of the paper consists of (very) simple examples of semantic descriptions in the various frameworks, illustrating the degree of reformulation needed when extending the described language|a strong indicator of modularity. Throughout, it is assumed that the reader has some familiarity with the concepts and notation of denotational and structural operational semantics. Familiarity with the basic notions of monads and monad transformers is not a prerequisite.

Semantics, Modularity, and Rewriting Logic

A complete formal semantic description of a practical programming language (such as Java) is likely to be a lengthy document, regardless of which semantic framework is being used. Good modularity of the description is important to the person(s) developing it, to facilitate reuse, change, and extension. Unfortunately, the conventional versions of the major semantic frameworks have rather poor modularity.In this paper, we first recall some approaches that improve the modularity of denotational semantics, namely action semantics, modular monadic semantics, and a hybrid framework that combines these: modular monadic action semantics. We then address the issue of modularity in operational semantics, which appears to have received comparatively little attention so far, and report on some preliminary investigations of how one might achieve the same kind of modularity in structural operational semantics as the use of monad transformers can provide in denotational semantics—this is the main technical contribution of the paper. Finally, we briefly consider the representation of structural operational semantics in rewriting logic, and speculate on the possibility of using it to interpret programs in the described language. Providing powerful meta-tools for such semantics-based interpretation is an interesting potential application of rewriting logic; good modularity of the semantic descriptions may be crucial for the practicality of using the tools.Much of the paper consists of (very) simple examples of semantic descriptions in the various frameworks, illustrating the degree of reformulation needed when extending the described language—a strong indicator of modularity. Throughout, it is assumed that the reader has some familiarity with the concepts and notation of denotational and structural operational semantics. Familiarity with the basic notions of monads and monad transformers is not a prerequisite.