Abstract not found

This paper surveys various complexity results on different forms of logic programming. The main focus is on decidable forms of logic programming, in particular, propositional logic programming and datalog, but we also mention general logic programming with function symbols. Next to classical results on plain logic programming (pure Horn clause programs), more recent results on various important extensions of logic programming are surveyed. These include logic programming with different forms of negation, disjunctive logic programming, logic programming with equality, and constraint logic programming. The complexity of the unification problem is also addressed.

This paper describes an implementation of narrowing, an essential component of implementations of modern functional logic languages. These implementations rely on narrowing, in particular on some optimal narrowing strategies, to execute functional logic programs. We translate functional logic programs into imperative (Java) programs without an intermediate abstract machine. A central idea of our approach is the explicit representation and processing of narrowing computations as data objects. This enables the implementation of operationally complete strategies (i.e., without backtracking) or techniques for search control (e.g., encapsulated search). Thanks to the use of an intermediate and portable representation of programs, our implementation is general enough to be used as a common back end for a wide variety of functional logic languages.

We propose a new computation model which combines the operational principles of functional languages (reduction), logic languages (non-deterministic search for solutions), and integrated functional logic languages (residuation and narrowing). This computation model combines efficient evaluation principles of functional languages with the problem-solving capabilities of logic programming. Since the model allows the delay of function calls which are not sufficiently instantiated, it also supports a concurrent style of programming. We provide soundness and completeness results and show that known evaluation principles of functional logic languages are particular instances of this model. Thus, our model is a suitable basis for future declarative programming languages.

Languages that integrate functional and logic programming with a complete operational semantics are based on narrowing, a unification-based goal-solving mechanism which subsumes the reduction principle of functional languages and the resolution principle of logic languages. Formal methods of transformation of functional logic programs can be based on this well-established operational semantics. In this paper, we present a partial evaluation scheme for functional logic languages based on an automatic unfolding algorithm which builds narrowing trees. We study the semantic properties of the transformation and the conditions under which the technique terminates, is sound and complete, and is also generally applicable to a wide class of programs. We illustrate our method with several examples and discuss the relation with Supercompilation and Partial Evaluation. To the best of our knowledge this is the first formal approach to partial evaluation of functional logic programs.

Abstract not found

Functional logic languages with a sound and complete operational semantics are mainly based on narrowing. Due to the huge search space of simple narrowing, steadily improved narrowing strategies have been developed in the past. Needed narrowing is currently the best narrowing strategy for first-order functional logic programs due to its optimality properties w.r.t. the length of derivations and the number of computed solutions. In this paper, we extend the needed narrowing strategy to higher-order functions and λ-terms as data structures. By the use of definitional trees, our strategy computes only incomparable solutions. Thus, it is the first calculus for higher-order functional logic programming which provides for such an optimality result. Since we allow higher-order logical variables denoting λ-terms, applications go beyond current functional and logic programming languages.

Abstract. In this paper we define an operational semantics for functional logic languages covering notions like laziness, sharing, concurrency, non-determinism, etc. Such a semantics is not only important to provide appropriate language definitions to reason about programs and check the correctness of implementations but it is also a basis to develop languagespecific tools, like program tracers, profilers, optimizers, etc. First, we define a "big-step " semantics in natural style to relate expressions and their evaluated results. Since this semantics is not sufficient to cover concurrency, search strategies, or to reason about costs associated to particular computations, we also define a "small-step " operational semantics covering the features of modern functional logic languages.

Escher is a general-purpose, declarative programming language that integrates the best features of both functional and logic programming languages. It has types and modules, higher-order and meta-programming facilities, concurrency, and declarative input/output. The main design aim is to combine in a practical and comprehensive way the best ideas of existing functional and logic languages, such as Haskell and Godel. In fact, Escher uses the Haskell syntax and is most straightforwardly understood as an extension of Haskell. Consequently, this paper discusses Escher from this perspective. It provides an introduction to the Escher language, concentrating largely on the issue of programming style and the Escher programming idioms not provided by Haskell. Also the extra mechanisms needed to support these idioms are discussed.

Abstract We introduce a novel approach for debugging ill-typed programs in the Hindley/Milner system. We map the typing problem for a program to a system of constraints each attached to program code that generates the constraints. We use reasoning about constraint satisfiability and implication to find minimal justifications of type errors, and to explain unexpected types that arise. Through an interactive process akin to declarative debugging, a user can track down exactly where a type error occurs. We are able to capture various extensions of the Hindley/Milner system such as type annotations and Haskell-style type class overloading. The approach has been implemented as part of the Chameleon system.