The CIL compiler for core Standard ML compiles whole programs using a novel typed intermediate language (TIL) with intersection and union types and ow labels on both terms and types. The CIL term representation duplicates portions of the program where intersection types are introduced and union types are eliminated. This duplication makes it easier to represent type information and to introduce customized data representations. However, duplication incurs compiletime space costs that are potentially much greater than are incurred in TILs employing type-level abstraction or quanti cation. In this paper, we present empirical data on the compile-time space costs of using CIL as an intermediate language. The data shows that these costs can be made tractable by using suciently ne-grained ow analyses together with standard hash-consing techniques. The data also suggests that nonduplicating formulations of intersection (and union) types would not achieve signi cantly better space complexity.

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Refactoring is a new name for a transformational approach to iterative software development. Originally focused on class diagrams, it is now commonly associated with object-oriented programming languages like Java. In this article, we trace some of the conceptual roots and the ideas behind refactoring, and sketch its relation to other techniques, such as behavioral and structural refinement or compiler optimization. Based on these observations, we firmly believe that improved and adapted refactoring techniques will belong to the methodical tool set of tomorrow's software engineers.

This paper proposes a non-standard way to combine lazy functional languages with I/O. In order to demonstrate the usefulness of the approach, a tiny lazy functional core language “FUNDIO”, which is also a call-by-need lambda calculus, is investigated. The syntax of “FUNDIO ” has case, letrec, constructors and an IO-interface: its operational semantics is described by small-step reductions. A contextual approximation and equivalence depending on the input-output behavior of normal order reduction sequences is defined and a context lemma is proved. This enables to study a semantics of “FUNDIO ” and its semantic properties. The paper demonstrates that the technique of complete reduction diagrams enables to show a considerable set of program transformations to be correct. Several optimizations of evaluation are given, including strictness optimizations and an abstract machine, and shown to be correct w.r.t. contextual equivalence. Correctness of strictness optimizations also justifies correctness of parallel evaluation. Thus this calculus has a potential to integrate non-strict functional programming with a non-deterministic approach to input-output and also to provide a useful semantics for this combination. It is argued that monadic IO and unsafePerformIO can be combined in Haskell, and that the result is reliable, if all reductions and transformations are correct w.r.t. to the FUNDIO-semantics. Of course, we do not address the typing problems the are involved in the usage of Haskell’s unsafePerformIO. The semantics can also be used as a novel semantics for strict functional languages with IO, where the sequence of IOs is not fixed.

The CIL compiler for core Standard ML compiles whole programs using the CIL typed intermediate language with ow labels and intersection and union types. Flow labels embed flow information in the types and intersection and union types support precise polyvariant type and flow information, without the use of type-level abstraction or quantification. Compile-time representations of CIL types and terms are potentially large compared to those for similar types and terms in systems based on quantified types. The listing-based nature of intersection and union types, together with flow label annotations on types, contribute to the size of CIL types. The CIL term representation duplicates portions of the program where intersection types are introduced and union types are eliminated. This duplication makes it easier to represent type information and to introduce multiple representation conventions, but incurs a compile-time space cost. This paper presents empirical data on the compile-time space cos...

Compilers for ML and Haskell typically go to a good deal of trouble to arrange that multiple arguments can be passed eciently to a procedure. For some reason, less effort seems to be invested in ensuring that multiple results can also be returned efficiently. In the context

Abstract. Vectorisation for functional programs, also called the flattening transformation, relies on drastically reordering computations and restructuring the representation of data types. As a result, it only applies to the purely functional core of a fully-fledged functional language, such as Haskell or ML. A concrete implementation needs to apply vectorisation selectively and integrate vectorised with unvectorised code. This is challenging, as vectorisation alters the data representation, which must be suitably converted between vectorised and unvectorised code. In this paper, we present an approach to partial vectorisation that selectively vectorises sub-expressions and data types, and also, enables linking vectorised with unvectorised modules.

The static single assignment (SSA) form is central to a range of optimisation algorithms relying on data flow information, and hence, to the correctness of compilers employing those algorithms. It is well known that the SSA form is closely related to lambda terms (i.e., functional programs), and, considering the large amount of energy expended on theories and frameworks for formal reasoning in the lambda calculus, it seems only natural to leverage this connection to improve our capabilities to reason about compiler optimisations. In this paper, we discuss a new formalisation of the mapping from SSA programs to a restricted form of lambda terms, called administrative normal form (ANF). We conjecture that this connection improves our ability to reason about SSA-based optimisation algorithms and provide a first data point by presenting an ANF variant of a well known SSA-based conditional constant propagation algorithm.

This paper is an extension of a previous work where two non-determinism analyses were presented. The first of them was efficient (linear) but not very powerful and the second one was more powerful but very expensive (exponential). Here, we develop an intermediate analysis in both aspects, efficiency and power. The improvement in efficiency is obtained by speeding up the fixpoint calculation by means of a widening operator, and the representation of functions through easily comparable signatures. Also details about the implementation and its cost are given. Additionally: (1) the second and third analyses are completed with polymorphism, (2) we prove that the domains in the second and third analyses form a category in which the morphisms are embedding-closure pairs of functions; respectively called abstraction and concretisation functions; and (3) we formally relate the analyses and prove that the first analysis is a safe approximation to the third one and that the third one is a safe approximation to the second one. In this way the three analyses become totally ordered by increasing cost and precision. 1

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