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Logic program specialisation through partial deduction: Control issues
 THEORY AND PRACTICE OF LOGIC PROGRAMMING
, 2002
"... Program specialisation aims at improving the overall performance of programs by performing source to source transformations. A common approach within functional and logic programming, known respectively as partial evaluation and partial deduction, is to exploit partial knowledge about the input. It ..."
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Cited by 56 (13 self)
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Program specialisation aims at improving the overall performance of programs by performing source to source transformations. A common approach within functional and logic programming, known respectively as partial evaluation and partial deduction, is to exploit partial knowledge about the input. It is achieved through a wellautomated application of parts of the BurstallDarlington unfold/fold transformation framework. The main challenge in developing systems is to design automatic control that ensures correctness, efficiency, and termination. This survey and tutorial presents the main developments in controlling partial deduction over the past 10 years and analyses their respective merits and shortcomings. It ends with an assessment of current achievements and sketches some remaining research challenges.
Offline specialisation in Prolog using a handwritten compiler generator
, 2004
"... The so called âcogen approachâ to program specialisation, writing a compiler generator instead of a specialiser, has been used with considerable success in partial evaluation of both functional and imperative languages. This paper demonstrates that this approach is also applicable to partial eva ..."
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Cited by 45 (23 self)
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The so called âcogen approachâ to program specialisation, writing a compiler generator instead of a specialiser, has been used with considerable success in partial evaluation of both functional and imperative languages. This paper demonstrates that this approach is also applicable to partial evaluation of logic programming languages, also called partial deduction. Selfapplication has not been as much in focus in logic programming as for functional and imperative languages, and the attempts to selfapply partial deduction systems have, of yet, not been altogether that successful. So, especially for partial deduction, the cogen approach should prove to have a considerable importance when it comes to practical applications. This paper first develops a generic offline partial deduction technique for pure logic programs, notably supporting partially instantiated datastructures via binding types. From this a very efficient cogen is derived, which generates very efficient generating extensions (executing up to several orders of magnitude faster than current online systems) which in turn perform very good and nontrivial specialisation, even rivalling existing online systems. All this is supported by extensive benchmarks. Finally, it is shown how the cogen can be extended to directly support a large part of Prologâs declarative and nondeclarative features and how semionline specialisation can be efficiently integrated.
Conjunctive Partial Deduction: Foundations, Control, Algorithms, and Experiments
 J. LOGIC PROGRAMMING
, 1999
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Specialization of Lazy Functional Logic Programs
 IN PROC. OF THE ACM SIGPLAN CONF. ON PARTIAL EVALUATION AND SEMANTICSBASED PROGRAM MANIPULATION, PEPM'97, VOLUME 32, 12 OF SIGPLAN NOTICES
, 1997
"... Partial evaluation is a method for program specialization based on fold/unfold transformations [8, 25]. Partial evaluation of pure functional programs uses mainly static values of given data to specialize the program [15, 44]. In logic programming, the socalled static/dynamic distinction is hard ..."
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Cited by 36 (21 self)
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Partial evaluation is a method for program specialization based on fold/unfold transformations [8, 25]. Partial evaluation of pure functional programs uses mainly static values of given data to specialize the program [15, 44]. In logic programming, the socalled static/dynamic distinction is hardly present, whereas considerations of determinacy and choice points are far more important for control [12]. We discuss these issues in the context of a (lazy) functional logic language. We formalize a twophase specialization method for a nonstrict, first order, integrated language which makes use of lazy narrowing to specialize the program w.r.t. a goal. The basic algorithm (first phase) is formalized as an instance of the framework for the partial evaluation of functional logic programs of [2, 3], using lazy narrowing. However, the results inherited by [2, 3] mainly regard the termination of the PE method, while the (strong) soundness and completeness results must be restated for the lazy strategy. A postprocessing renaming scheme (second phase) is necessary which we describe and illustrate on the wellknown matching example. This phase is essential also for other nonlazy narrowing strategies, like innermost narrowing, and our method can be easily extended to these strategies. We show that our method preserves the lazy narrowing semantics and that the inclusion of simplification steps in narrowing derivations can improve control during specialization.
Conjunctive Partial Deduction in Practice
 Proceedings of the International Workshop on Logic Program Synthesis and Transformation (LOPSTR'96), LNCS 1207
, 1996
"... . Recently, partial deduction of logic programs has been extended to conceptually embed folding. To this end, partial deductions are no longer computed of single atoms, but rather of entire conjunctions; Hence the term "conjunctive partial deduction". Conjunctive partial deduction aims at ..."
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Cited by 27 (20 self)
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. Recently, partial deduction of logic programs has been extended to conceptually embed folding. To this end, partial deductions are no longer computed of single atoms, but rather of entire conjunctions; Hence the term "conjunctive partial deduction". Conjunctive partial deduction aims at achieving unfold/foldlike program transformations such as tupling and deforestation within fully automated partial deduction. However, its merits greatly surpass that limited context: Also other major efficiency improvements are obtained through considerably improved sideways information propagation. In this extended abstract, we investigate conjunctive partial deduction in practice. We describe the concrete options used in the implementation(s), look at abstraction in a practical Prolog context, include and discuss an extensive set of benchmark results. From these, we can conclude that conjunctive partial deduction indeed pays off in practice, thoroughly beating its conventional precursor on a wide...
A conceptual embedding of folding into partial deduction: Towards a maximal integration
, 1996
"... The relation between partial deduction and the unfold/fold approach has been a matter of intense discussion. In this paper we consolidate the advantages of the two approaches and provide an extended partial deduction framework in which most of the tupling and deforestation transformations of the fol ..."
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Cited by 25 (13 self)
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The relation between partial deduction and the unfold/fold approach has been a matter of intense discussion. In this paper we consolidate the advantages of the two approaches and provide an extended partial deduction framework in which most of the tupling and deforestation transformations of the fold/unfold approach, as well the current partial deduction transformations, can be achieved. Moreover, most of the advantages of partial deduction, e.g. lower complexity and a more detailed understanding of control issues, are preserved. We build on welldefined concepts in partial deduction and present a conceptual embedding of folding into partial deduction, called conjunctive partial deduction. Two minimal extensions to partial deduction are proposed: using conjunctions of atoms instead of atoms as the principle specialisation entity and also renaming conjunctions of atoms instead of individual atoms. Correctness results for the extended framework (with respect to computed answer semantics and finite failure semantics) are given. Experiments with a prototype implementation are presented, showing that, somewhat to our surprise, conjunctive partial deduction not only handles the removal of unnecessary variables, but also leads to substantial improvements in specialisation for standard partial deduction examples. 1
Constrained Partial Deduction and the Preservation of Characteristic Trees
 NEW GENERATION COMPUTING
, 1997
"... Partial deduction strategies for logic programs often use an abstraction operator to guarantee the finiteness of the set of goals for which partial deductions are produced. Finding an abstraction operator which guarantees finiteness and does not lose relevant information is a difficult problem. I ..."
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Cited by 21 (16 self)
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Partial deduction strategies for logic programs often use an abstraction operator to guarantee the finiteness of the set of goals for which partial deductions are produced. Finding an abstraction operator which guarantees finiteness and does not lose relevant information is a difficult problem. In earlier work Gallagher and Bruynooghe proposed to base the abstraction operator on characteristic paths and trees, which capture the structure of the generated incomplete SLDNFtree for a given goal. In this paper we exhibit the advantages of characteristic trees over purely syntactical measures: if characteristic trees can be preserved upon generalisation, then we obtain an almost perfect abstraction operator, providing just enough polyvariance to avoid any loss of local specialisation. Unfortunately, the abstraction operators proposed in earlier work do not always preserve the characteristic trees upon generalisation. We show that this can lead to important specialisation losses as well as to nontermination of the partial deduction algorithm. Furthermore, this problem cannot be adequately solved in the ordinary partial deduction setting. We therefore extend the expressivity and precision of the Lloyd and Shepherdson partial deduction framework by integrating constraints. We provide formal correctness results for the so obtained generic framework of constrained partial deduction. Within this new framework we are, among others, able to overcome the above mentioned problems by introducing an alternative abstraction operator, based on so called pruning constraints. We thus present a terminating partial deduction strategy which, for purely determinate unfolding rules, induces no loss of local specialisation due to the abstraction while ensuring correctness o...
Advanced Logic Program Specialisation
 In this volume
"... Declarative programming languages, are highlevel programming languages in which one only has to state what is to be computed and not necessarily how it is to be computed. Logic programming and functional programming are two prominent members of this class of programming languages. While functional ..."
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Cited by 20 (11 self)
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Declarative programming languages, are highlevel programming languages in which one only has to state what is to be computed and not necessarily how it is to be computed. Logic programming and functional programming are two prominent members of this class of programming languages. While functional programming is based on the calculus, logic
Decompilation of Java Bytecode to Prolog by Partial Evaluation
, 2009
"... Reasoning about Java bytecode (JBC) is complicated due to its unstructured controlflow, the use of threeaddress code combined with the use of an operand stack, etc. Therefore, many static analyzers and model checkers for JBC first convert the code into a higherlevel representation. In contrast to ..."
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Cited by 14 (8 self)
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Reasoning about Java bytecode (JBC) is complicated due to its unstructured controlflow, the use of threeaddress code combined with the use of an operand stack, etc. Therefore, many static analyzers and model checkers for JBC first convert the code into a higherlevel representation. In contrast to traditional decompilation, such representation is often not Java source, but rather some intermediate language which is a good input for the subsequent phases of the tool. Interpretive decompilation consists in partially evaluating an interpreter for the compiled language (in this case JBC) written in a highlevel language w.r.t. the code to be decompiled. There have been proofsofconcept that interpretive decompilation is feasible, but there remain important open issues when it comes to decompile a real language such as JBC. This paper presents, to the best of our knowledge, the first modular scheme to enable interpretive decompilation of a realistic programming language to a highlevel representation, namely of JBC to Prolog. We introduce two notions of optimality which together require that decompilation does not generate code more than once for each program point. We demonstrate the impact of our modular approach and optimality issues on a series of realistic benchmarks. Decompilation times and decompiled program sizes are linear with the size of the input bytecode program. This demonstrates empirically the scalability of modular decompilation of JBC by partial evaluation.
A Constraintbased Partial Evaluator for Functional Logic Programs and its Application
, 1998
"... The aim of this work is the development and application of a partial evaluation procedure for rewritingbased functional logic programs. Functional logic programming languages unite the two main declarative programming paradigms. The rewritingbased computational model extends traditional functional ..."
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Cited by 12 (0 self)
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The aim of this work is the development and application of a partial evaluation procedure for rewritingbased functional logic programs. Functional logic programming languages unite the two main declarative programming paradigms. The rewritingbased computational model extends traditional functional programming languages by incorporating logical features, including logical variables and builtin search, into its framework. This work is the first to address the automatic specialisation of these functional logic programs. In particular, a theoretical framework for the partial evaluation of rewritingbased functional logic programs is defined and its correctness is established. Then, an algorithm is formalised which incorporates the theoretical framework for the procedure in a fully automatic technique. Constraint solving is used to represent additional information about the terms encountered during the transformation in order to improve the efficiency and size of the residual programs. ...