Linear type systems permit programmers to deallocate or explicitly recycle memory, but they are severly restricted by the fact that they admit no aliasing. This paper describes a pseudo-linear type system that allows a degree of aliasing and memory reuse as well as the ability to define complex recursive data structures. Our type system can encode conventional linear data structures such as linear lists and trees as well as more sophisticated data structures including cyclic and doubly-linked lists and trees. In the latter cases, our type system is expressive enough to represent pointer aliasing and yet safely permit destructive operations such as object deallocation. We demonstrate the flexibility of our type system by encoding two common compiler optimizations: destination-passing style and Deutsch-Schorr-Waite or "link-reversal" traversal algorithms.

Strong normalization results are obtained for a general language for collection types. An induced normal form for sets and bags is then used to show that the class of functions whose input has height (that is, the maximal depth of nestings of sets/bags/lists in the complex object) at most i and output has height at most o definable in a nested relational query language without powerset operator is independent of the height of intermediate expressions used. Our proof holds regardless of whether the language is used for querying sets, bags, or lists, even in the presence of variant types. Moreover, the normal forms are useful in a general approach to query optimization. Paredaens and Van Gucht proved a similar result for the special case when i = o = 1. Their result is complemented by Hull and Su who demonstrated the failure of independence when powerset operator is present and i = o = 1. The theorem of Hull and Su was generalized to all i and o by Grumbach and Vianu. Our result genera...

Needed narrowing is a complete operational principle for modern declarative languages which integrate the best features of (lazy) functional and logic programming. We define a transformation methodology for functional logic programs based on needed narrowing. We provide (strong) correctness results for the transformation system w.r.t. the set of computed values and answer substitutions and show that the prominent properties of needed narrowing -- namely, the optimality w.r.t. the length of derivations and the number of computed solutions -- carry over to the transformation process and the transformed programs. We illustrate the power of the system by taking on in our setting two well-known transformation strategies (composition and tupling). We also provide an implementation of the transformation system which, by means of some experimental results, highlights the benefits of our approach.

Strong normalization results are obtained for a general language for collection types. An induced normal form for sets and bags is then used to show that the class of functions whose input has height (that is, the maximal depth of nestings of sets/bags/lists in the complex object) at most i and output has height at most o definable in a nested relational query language without powerset operator is independent of the height of intermediate expressions used. Our proof holds regardless of whether the language is used for querying sets, bags, or lists, even in the presence of variant types. Moreover, the normal forms are useful in a general approach to query optimization. Paredaens and Van Gucht proved a similar result for the special case when i = o = 1. Their result is complemented by Hull and Su who demonstrated the failure of independence when powerset operator is present and i = o = 1. The theorem of Hull and Su was generalized to all i and o by Grumbach and Vianu. Our result generali...

Wadler's deforestation algorithm eliminates intermediate data structures from functional programs. To be suitable for inclusion in a compiler, it must terminate on all programs. Several techniques to ensure termination of deforestation on all first-order programs are known, but a technique for higher-order programs was only recently introduced by Hamilton, and elaborated and implemented in the Glasgow Haskell compiler by Marlow. We introduce a new technique for ensuring termination of deforestation on all higher-order programs that allows useful transformation steps prohibited in Hamilton's and Marlowe's techniques. 1 Introduction Lazy, higher-order, functional programming languages lend themselves to a certain style of programming which uses intermediate data structures [28]. Example 1 Consider the following program. letrec a = x; y:case x of [] ! y (h : t) ! h : a t y in u; v; w: a (a u v) w The term u; v; w:a (a u v) w appends the three lists u, v, and w. Appending u and v ...

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.

This work introduces a transformation methodology for functional logic programs based on needed narrowing, the optimal and complete operational principle for modern declarative languages which integrate the best features of functional and logic programming. We provide correctness results for the transformation system w.r.t. the set of computed values and answer substitutions and show that the prominent properties of needed narrowing—namely, the optimality w.r.t. the length of derivations and the number of computed solutions—carry over to the transformation process and the transformed programs. We illustrate the power of the system by taking on in our setting two well-known transformation strategies (composition and tupling). We also provide an implementation of the transformation system which, by means of some experimental results, highlights the potentiality of our approach.

Abstract. Modular programming enjoys many well-known advantages but the composition of modular units may also lead to inefficient programs. In this paper, we propose an invasive composition method which strives to reconcile modularity and efficiency. Our technique, network fusion, automatically merges networks of interacting components into equivalent sequential programs. We provide the user with an expressive language to specify scheduling constraints which can be taken into account during network fusion. Fusion allows to replace internal communications by assignments and alleviates most time overhead. We present our approach in a generic and unified framework based on labeled transition systems, static analysis and transformation techniques. 1

In functional programming, small programs are often combined to construct larger, more complex ones. The component reuse encouraged by this modular style of programming yields many benefits, but, unfortunately, modular programs also tend to be less efficient than their monolithic counterparts. Inefficiency is significantly attributable to the construction of intermediate data structures which "glue" together the smaller program components into larger ones. Fusion is the process of removing intermediate data structures from modularly constructed programs. Two particularly successful approaches to achieving fusion in functional languages have emerged in recent years. The first is a catamorphic fusion technique based on the promotion theorems of category theory. The second is a shortcut based on parametricity which fuses compositional programs via canned applications of traditional fold/unfold program transformation steps. Both techniques apply only to programs written in terms ...

Needed narrowing is an optimal and complete operational principle for modern declarative languages which integrate the best features of (lazy) functional and logic programming. We define a transformation methodology for functional logic programs based on needed narrowing. We provide (strong) correctness results for the transformation system w.r.t. the set of computed values and answer substitutions and show that the prominent properties of needed narrowing carry over to the transformation process and the transformed programs. We illustrate the power of the system by taking on in our setting two well-known transformation strategies (composition and tupling). We also provide an implementation of the transformation system which, by means of some experimental results, highlights the benefits of our approach.