This paper describes a scheme for constructing parsers based on the top-down combinator approach. In particular, it describes a set of combinators for parsing expressions described by ambiguous grammars with precedence and associativity rules. The new combinators embody the mechanical grammar manipulations typically employed to remove left-recursion and hence help to avoid the possibility of a non-terminating parser. A number of approaches to the problem are described—the most elegant and efficient method is based on continuation passing. As a practical demonstration, a parser for the expression part of the C programming language is presented. The expression combinators are general, and may be constructed from any suitable set of top-down combinators. A comparison with parser generators shows that the combinator approach is most applicable for rapid development.

Most major OS kernels today run on multiprocessor systems and are preemptive: it is possible for a process running in the kernel mode to get descheduled. Existing modular techniques for verifying concurrent code are not directly applicable in this setting: they rely on scheduling being implemented correctly, and in a preemptive kernel, the correctness of the scheduler is interdependent with the correctness of the code it schedules. This interdependency is even stronger in mainstream kernels, such as those of Linux, FreeBSD or Mac OS X, where the scheduler and processes interact in complex ways. We propose the first logic that is able to decompose the verification of preemptive multiprocessor kernel code into verifying the scheduler and the rest of the kernel separately, even in the presence of complex interdependencies between the two components. The logic hides the manipulation of control by the scheduler when reasoning about preemptable code and soundly inherits proof rules from concurrent separation logic to verify it thread-modularly. We illustrate the power of our logic by verifying an example scheduler, which includes some of the key features of the scheduler from Linux 2.6.11 challenging for verification.

Traditional functional languages do not have an explicit distinction between binding times. It arises implicitly, however, as one typically instantiates a higher-order function with the arguments that are known, whereas the unknown arguments remain to be taken as parameters. The distinction between ‘known’ and ‘unknown’ is closely related to the distinction between binding times like ‘compile-time’ and ‘run-time’. This leads to the use of a combination of polymorphic type inference and binding time analysis for obtaining the required information about which arguments are known.

Following the current trend in the implementation of functional languages we then transform the run-time level of the program (not the compile-time level) into categorical combinators. At this stage we have a natural distinction between two kinds of program transformations: partial evaluation, which involves the compile-time level of our notation, and algebraic transformations (i.e., the application of algebraic laws), which involves the run-time level of our notation.

By reinterpreting the combinators in suitable ways we obtain specifications of abstract interpretations (or data flow analyses). In particular, the use of combinators makes it possible to use a general framework for specifying both forward and backward analyses. The results of these analyses will be used to enable program transformations that are not applicable under all circumstances.

Finally, the combinators can also be reinterpreted to specify code generation for various (abstract) machines. To improve the efficiency of the code generated, one may apply abstract interpretations to collect extra information for guiding the code generation. Peephole optimizations may be used to improve the code at the lowest level.

This paper presents semantic specifications and correctness proofs for both on-line and offline partial evaluation of strict first-order functional programs. To do so, our strategy consists of defining a core semantics as a basis for the specification of three non-standard evaluations: instrumented evaluation, on-line and off-line partial evaluation. We then use the technique of logical relations to prove the correctness of both on-line and off-line partial evaluation semantics.

The contributions of this work are as follows:

1. We provide a uniform framework to defining and proving correct both on-line and off-line partial evaluation.

2. This work required a formal specification of on-line partial evaluation with polyvariant specialization. We define criteria for its correctness with respect to an instrumented standard semantics. As a by-product, on-line partial evaluation appears to be based on a fixpoint iteration process, just like binding-time analysis.

3. We show that binding-time analysis, the preprocessing phase of off-line partial evaluation, is an abstraction of on-line partial evaluation. Therefore, its correctness can be proved with respect to on-line partial evaluation, instead of with respect to the standard semantics, as is customarily done.

4. Based on the binding-time analysis, we formally derive the specialization semantics for off-line partial evaluation. This strategy ensures the correctness of the resulting semantics.

This paper shows how to reason about streams concisely and precisely. Streams, infinite sequences of elements, live in a coworld: they are given by a coinductive datatype, operations on streams are implemented by corecursive programs, and proofs are typically concocted using coinduction. This paper offers an alternative to coinduction. Suitably restricted, stream equations possess unique solutions. This property gives rise to a simple and attractive proof technique, essentially bringing equational reasoning to the coworld. We redevelop the theory of recurrences, finite calculus and generating functions using streams and stream operators, building on the cornerstone of unique solutions. The paper contains a smörgåsbord of examples: we study recursion elimination, investigate the binary carry sequence, explore Sprague-Grundy numbers and present two proofs of Moessner's Theorem. The calculations benefit from the rich structure of streams. As the type of streams is an applicative functor we can effortlessly lift operations and their properties to streams. In combination with Haskell's facilities for overloading, this greatly contributes to conciseness of notation. The development is indeed constructive: streams and stream operators are implemented in Haskell, usually by one-liners. The resulting calculus or library, if you wish, is elegant and fun to use.

We have developed a simple algebraic approach to music description and composition called Haskore. In this framework, musical objects consist of primitive notions such as notes and rests, operations to transform musical objects such as transpose and tempo-scaling, and operations to combine musical objects to form more complex ones, such as concurrent and sequential composition. When these simple notions are embedded into a functional language such as Haskell, rather complex musical relationships can be expressed clearly and succinctly. Exploiting the algebraic properties of Haskore, we have further defined a notion of literal performance (devoid of articulation) through which observationally equivalent musical objects can be determined. With this basis many useful properties can be proved, such as commutative, associative, and distributive properties of various operators. An algebra of music thus surfaces.

An extension of ML with continuation primitives similar to those found in Scheme is considered. A number of alternative type systems are discussed, and several programming examples are given. A continuation-based operational semantics is defined for a small, purely functional language, and the soundness of the Damas–Milner polymorphic type assignment system with respect to this semantics is proved. The full Damas–Milner type system is shown to be unsound in the presence of first-class continuations. Restrictions on polymorphism similar to those introduced in connection with reference types are shown to suffice for soundness.

Arrows are a popular form of abstract computation. Being more general than monads, they are more broadly applicable, and, in particular, are a good abstraction for signal processing and dataflow computations. Most notably, arrows form the basis for a domain-specific language called Yampa, which has been used in a variety of concrete applications, including animation, robotics, sound synthesis, control systems, and graphical user interfaces. Our primary interest is in better understanding the class of abstract computations captured by Yampa. Unfortunately, arrows are not concrete enough to do this with precision. To remedy this situation, we introduce the concept of commutative arrows that capture a noninterference property of concurrent computations. We also add an init operator that captures the causal nature of arrow effects, and identify its associated law. To study this class of computations in more detail, we define an extension to arrows called causal commutative arrows (CCA), and study its properties. Our key contribution is the identification of a normal form for CCA called causal commutative normal form (CCNF). By defining a normalization procedure, we have developed an optimization strategy that yields dramatic improvements in performance over conventional implementations of arrows. We have implemented this technique in Haskell, and conducted benchmarks that validate the effectiveness of our approach. When compiled with the Glasgow Haskell Compiler (GHC), the overall methodology can result in significant speedups.

Combinatorial search strategies including depth-first, breadth-first and depth-bounded search are shown to be different implementations of a common algebraic specification that emphasizes the compositionality of the strategies. This specification is placed in a categorical setting that combines algebraic specifications and monads.

This paper presents a simple framework for performing calculations with the elements of (finite) lattices. A particular feature of this work is the use of type classes to enable the use of overloaded function symbols within a strongly typed language. Previous applications of type classes have been in areas that are of most interest to language implementors. This paper suggests that type classes might also be useful as a general tool in the development of clear and modular programs.

Reasoning about program equivalence is one of the oldest problems in semantics. In recent years, useful techniques have been developed, based on bisimulations and logical relations, for reasoning about equivalence in the setting of increasingly realistic languages—languages nearly as complex as ML or Haskell. Much of the recent work in this direction has considered the interesting representation independence principles enabled by the use of local state, but it is also important to understand the principles that powerful features like higher-order state and control effects disable. This latter topic has been broached extensively within the framework of game semantics, resulting in what Abramsky dubbed the “semantic cube”: fully abstract game-semantic characterizations of various axes in the design space of ML-like languages. But when it comes to reasoning about many actual examples, game semantics does not yet supply a useful technique for proving equivalences.

In this paper, we marry the aspirations of the semantic cube to the powerful proof method of step-indexed Kripke logical relations. Building on recent work of Ahmed et al. (2009), we define the first fully abstract logical relation for an ML-like language with recursive types, abstract types, general references and call/cc. We then show how, under orthogonal restrictions to the expressive power of our language—namely, the restriction to first-order state and/or the removal of call/cc—we can enhance the proving power of our possible-worlds model in correspondingly orthogonal ways, and we demonstrate this proving power on a range of interesting examples. Central to our story is the use of state transition systems to model the way in which properties of local state evolve over time.

Unfolding is a common technique in program transformations. Here, we present a computation model where unfolding is a simple generalisation of the usual concept of evaluation. The model is a variant of the well-known full substitution evaluation rule for recursive programs. The evaluation mechanism involved is symbolic substitution of function definitions followed by simplification. Simplification is expressed as a confluent rewrite strategy which uses three kinds of reductions: β-reduction, non-erasing reduction, and erasing reduction. Non-erasing reductions include simplification of constant subexpressions. Erasing reductions formalize the behaviour of nonstrict operations. In this computation model, we prove a termination theorem of symbolic unfolding relative to more instantiated calls. A possible application of the model is a technique called total unfolding, where a partially instantiated function call is unfolded until no more calls exist. Under certain conditions the result will be a first order term: such terms correspond to basic blocks in imperative programs and can be efficiently implemented by scheduling techniques. Possible applications are hardware synthesis, and code generation for parallel machines.

We argue that the novel combination of type classes and existential types in a single language yields significant expressive power. We explore this combination in the context of higher-order functional languages with static typing, parametric polymorphism, algebraic data types and Hindley–Milner type inference. Adding existential types to an existing functional language that already features type classes requires only a minor syntactic extension. We first demonstrate how to provide existential quantification over type classes by extending the syntax of algebraic data type definitions, and give examples of possible uses. We then develop a type system and a type inference algorithm for the resulting language. Finally, we present a formal semantics by translation to an implicitly-typed second-order λ-calculus and show that the type system is semantically sound. Our extension has been implemented in the Chalmers Haskell B. system, and all examples from this paper have been developed using this system.

This paper provides a formal treatment of isomorphic types for languages equipped with an ML style polymorphic type inference mechanism. The results obtained make less justified the commonplace feeling that (the core of) ML is a subset of second order λ-calculus: we can provide an isomorphism of types that holds in the core ML language, but not in second order λ-calculus. This new isomorphism allows to provide a complete (and decidable) axiomatization of all the types isomorphic in ML style languages, a relevant issue for the type as specifications paradigm in library searches. This work is a very extended version of Di Cosmo (1992): we provide both a thorough theoretical treatment of the topic and describe a practical implementation of a library search system so that the paper can be used as a reference both by those interested in the formal theory of ML style languages, and by those simply concerned with implementation issues. The new isomorphism can also be used to extend the usual ML type-inference algorithm, as suggested by Di Cosmo (1992). Building on that proposal, we introduce a better type-inference algorithm that behaves well in the presence of non-functional primitives like references and exceptions. The algorithm described here has been implemented easily as a variation to the Caml-Light 0.4 system.

Type abstraction and intensional type analysis are features seemingly at odds—type abstraction is intended to guarantee parametricity and representation independence, while type analysis is inherently non-parametric. Recently, however, several researchers have proposed and implemented “dynamic type generation” as a way to reconcile these features. The idea is that, when one defines an abstract type, one should also be able to generate at runtime a fresh type name, which may be used as a dynamic representative of the abstract type for purposes of type analysis. The question remains: in a language with non-parametric polymorphism, does dynamic type generation provide us with the same kinds of abstraction guarantees that we get from parametric polymorphism?

Our goal is to provide a rigorous answer to this question. We define a step-indexed Kripke logical relation for a language with both non-parametric polymorphism (in the form of type-safe cast) and dynamic type generation. Our logical relation enables us to establish parametricity and representation independence results, even in a non-parametric setting, by attaching arbitrary relational interpretations to dynamically generated type names. In addition, we explore how programs that are provably equivalent in a more traditional parametric logical relation may be “wrapped” systematically to produce terms that are related by our non-parametric relation, and vice versa. This leads us to develop a “polarized” variant of our logical relation, which enables us to distinguish formally between positive and negative notions of parametricity.

Self-applicable specializers have been used successfully to automate the generation of compilers. Specializers are often rather sophisticated, for which reason one would like to adapt and transform them with the aid of the computer. But how to automate this process? The answer to this question is given by three specializer projections. While the Futamura projections define the generation of compilers from interpreters, the specializer projections define the generation of specializers from interpreters. We discuss the potential applications of the specializer projections, and argue that their realization is a real touchstone for the effectiveness of the specialization principle. In particular, we discuss generic specializers, bootstrapping of subject languages and the generation of optimizing specializers from interpretive specifications. The Futamura projections are regarded as a special case of the specializer projections. Recent results confirm that the specializer projections can be performed in practice using partial evaluators.

Monitoring semantics is a formal model of program execution which captures ‘monitoring activity’ as found in profilers, tracers, debuggers, etc. Beyond its theoretical interest, this formalism provides a new methodology for implementing a large family of source-level monitoring activities for sequential deterministic programming languages. In this article we explore the use of monitoring semantics in the specification and implementation of a variety of monitors: profilers, tracers, collecting interpreters, and, most importantly, interactive source-level debuggers. Although we consider such monitors only for (both strict and non-strict) functional languages, the methodology extends easily to imperative languages, since it begins with a continuation semantics specification.

In addition, using standard partial evaluation techniques as an optimization strategy, we show that the methodology forms a practical basis for building real monitors. Our system can be optimized at two levels of specialization: specializing the interpreter with respect to a monitor specification automatically yields an instrumented interpreter; further specializing this instrumented interpreter with respect to a source program yields an instrumented program, i.e. one in which the extra code to perform monitoring has been automatically embedded into the program.

This paper proves correctness of Nöcker's method of strictness analysis, implemented in the Clean compiler, which is an effective way for strictness analysis in lazy functional languages based on their operational semantics. We improve upon the work Clark, Hankin and Hunt did on the correctness of the abstract reduction rules in two aspects. Our correctness proof is based on a functional core language and a contextual semantics, thus proving a wider range of strictness-based optimizations as correct, and our method fully considers the cycle detection rules, which contribute to the strength of Nöcker's strictness analysis.

Our algorithm SAL is a reformulation of Nöcker's strictness analysis algorithm in a functional core language LR. This is a higher order call-by-need lambda calculus with case, constructors, letrec, and seq, which is extended during strictness analysis by set constants like Top or Inf, denoting sets of expressions, which indicate different evaluation demands. It is also possible to define new set constants by recursive equations with a greatest fixpoint semantics. The operational semantics of LR is a small-step semantics. Equality of expressions is defined by a contextual semantics that observes termination of expressions. Basically, SAL is a nontermination checker. The proof of its correctness and hence of Nöcker's strictness analysis is based mainly on an exact analysis of the lengths of evaluations, i.e., normal-order reduction sequences to WHNF. The main measure being the number of “essential” reductions in evaluations.

Our tools and results provide new insights into call-by-need lambda calculi, the role of sharing in functional programming languages, and into strictness analysis in general. The correctness result provides a foundation for Nöcker's strictness analysis in Clean, and also for its use in Haskell.

In this paper we show that it is possible to implement a symmetric set of finite-list operations efficiently; the set is symmetric in the sense that lists can be manipulated at either end. We derive the definitions of these operations from their specifications by calculation. The operations have O(1) time complexity, provided that we content ourselves with, so-called, amortized efficiency, instead of worst-case efficiency

We have built the first family of tagless interpretations for a higher-order typed object language in a typed metalanguage (Haskell or ML) that require no dependent types, generalized algebraic data types, or postprocessing to eliminate tags. The statically type-preserving interpretations include an evaluator, a compiler (or staged evaluator), a partial evaluator, and call-by-name and call-by-value continuation-passing style (CPS) transformers. Our principal technique is to encode de Bruijn or higher-order abstract syntax using combinator functions rather than data constructors. In other words, we represent object terms not in an initial algebra but using the coalgebraic structure of the λ-calculus. Our representation also simulates inductive maps from types to types, which are required for typed partial evaluation and CPS transformations. Our encoding of an object term abstracts uniformly over the family of ways to interpret it, yet statically assures that the interpreters never get stuck. This family of interpreters thus demonstrates again that it is useful to abstract over higher-kinded types.