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Tutorial Notes on Partial Evaluation
 Proceedings of the Twentieth Annual ACM Symposium on Principles of Programming Languages
, 1993
"... The last years have witnessed a flurry of new results in the area of partial evaluation. These tutorial notes survey the field and present a critical assessment of the state of the art. 1 Introduction Partial evaluation is a sourcetosource program transformation technique for specializing program ..."
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Cited by 237 (62 self)
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The last years have witnessed a flurry of new results in the area of partial evaluation. These tutorial notes survey the field and present a critical assessment of the state of the art. 1 Introduction Partial evaluation is a sourcetosource program transformation technique for specializing programs with respect to parts of their input. In essence, partial evaluation removes layers of interpretation. In the most general sense, an interpreter can be defined as a program whose control flow is determined by its input data. As Abelson points out, [43, Foreword], even programs that are not themselves interpreters have important interpreterlike pieces. These pieces contain both compiletime and runtime constructs. Partial evaluation identifies and eliminates the compiletime constructs. 1.1 A complete example We consider a function producing formatted text. Such functions exist in most programming languages (e.g., format in Lisp and printf in C). Figure 1 displays a formatting functio...
A System For Specialising Logic Programs
, 1991
"... This report describes SP, a system for specialising logic programs. The report functions as a user's manual for SP, and also contains the algorithms employed and arguments for their correctness. A number of examples of program specialisation are given in Appendix A. Contents 1 Program Specialisation ..."
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Cited by 147 (12 self)
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This report describes SP, a system for specialising logic programs. The report functions as a user's manual for SP, and also contains the algorithms employed and arguments for their correctness. A number of examples of program specialisation are given in Appendix A. Contents 1 Program Specialisation 4 2 Transformations in SP 5 3 Unfolding Rules 10 4 Approximation 13 5 The Specialisation Algorithm 16 6 How to Use SP 20 7 Discussion 23 A Examples of Specialisation 28 B Unfoldability Conditions for Builtins 36 1 Program Specialisation SP is a system for specialising logic programs. Before describing the system, it is worth reviewing briefly the aims and interesting applications of program specialisation. To specialise a program is to restrict its behaviour in some way. The purpose of specialisation is to exploit the restriction to gain efficiency. A specialised program is equivalent, within the bounds of the restriction imposed, to the original unspecialised program, but should be ...
An Introduction to Partial Evaluation
 ACM Computing Surveys
, 1996
"... Partial evaluation provides a unifying paradigm for a broad spectrum of work in ..."
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Cited by 134 (0 self)
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Partial evaluation provides a unifying paradigm for a broad spectrum of work in
SSemantics Approach: Theory and Applications
, 1994
"... The paper is a general overview of an approach to the semantics of logic programs whose aim is finding notions of models which really capture the operational semantics, and are therefore useful for defining program equivalences and for semanticsbased program analysis. The approach leads to the intr ..."
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Cited by 115 (26 self)
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The paper is a general overview of an approach to the semantics of logic programs whose aim is finding notions of models which really capture the operational semantics, and are therefore useful for defining program equivalences and for semanticsbased program analysis. The approach leads to the introduction of extended interpretations which are more expressive than Herbrand interpretations. The semantics in terms of extended interpretations can be obtained as a result of both an operational (topdown) and a fixpoint (bottomup) construction. It can also be characterized from the modeltheoretic viewpoint, by defining a set of extended models which contains standard Herbrand models. We discuss the original construction modeling computed answer substitutions, its compositional version and various semantics modeling more concrete observables. We then show how the approach can be applied to several extensions of positive logic programs. We finally consider some applications, mainly in the area of semanticsbased program transformation and analysis.
Acquiring SearchControl Knowledge via Static Analysis
 Artificial Intelligence
, 1993
"... ExplanationBased Learning (EBL) is a widelyused technique for acquiring searchcontrol knowledge. Recently, Prieditis, van Harmelen, and Bundy pointed to the similarity between Partial Evaluation (PE) and EBL. However, EBL utilizes training examples whereas PE does not. It is natural to inquire, th ..."
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Cited by 87 (2 self)
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ExplanationBased Learning (EBL) is a widelyused technique for acquiring searchcontrol knowledge. Recently, Prieditis, van Harmelen, and Bundy pointed to the similarity between Partial Evaluation (PE) and EBL. However, EBL utilizes training examples whereas PE does not. It is natural to inquire, therefore, whether PE can be used to acquire searchcontrol knowledge, and if so at what cost? This paper answers these questions by means of a case study comparing prodigy/ebl, a stateoftheart EBL system, and static, a PEbased analyzer of problemspace definitions. When tested in prodigy/ebl's benchmark problem spaces, static generated searchcontrol knowledge that was up to three times as effective as the knowledge learned by prodigy/ebl, and did so from twentysix to seventyseven times faster. The paper describes static's algorithms, compares its performance to prodigy/ebl's, noting when static's superior performance will scale up and when it will not. The paper concludes with several le...
A Science of Reasoning
, 1991
"... This paper addresses the question of how we can understand reasoning in general and mathematical proofs in particular. It argues the need for a highlevel understanding of proofs to complement the lowlevel understanding provided by Logic. It proposes a role for computation in providing this high ..."
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Cited by 74 (19 self)
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This paper addresses the question of how we can understand reasoning in general and mathematical proofs in particular. It argues the need for a highlevel understanding of proofs to complement the lowlevel understanding provided by Logic. It proposes a role for computation in providing this highlevel understanding, namely by the association of proof plans with proofs. Proof plans are defined and examples are given for two families of proofs. Criteria are given for assessing the association of a proof plan with a proof. 1 Motivation: the understanding of mathematical proofs The understanding of reasoning has interested researchers since, at least, Aristotle. Logic has been proposed by Aristotle, Boole, Frege and others as a way of formalising arguments and understanding their structure. There have also been psychological studies of how people and animals actually do reason. The work on Logic has been especially influential in the automation of reasoning. For instance, resolution...
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 54 (12 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.
MetaProgramming in Logic Programming
 Handbook of Logic in Artificial Intelligence and Logic Programming
, 1994
"... data types are facilitated in Godel by its type and module systems. Thus, in order to describe the metaprogramming facilities of Godel, a brief account of these systems is given. Each constant, function, predicate, and proposition in a Godel program must be specified by a language declaration. The ..."
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Cited by 46 (3 self)
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data types are facilitated in Godel by its type and module systems. Thus, in order to describe the metaprogramming facilities of Godel, a brief account of these systems is given. Each constant, function, predicate, and proposition in a Godel program must be specified by a language declaration. The type of a variable is not declared but inferred from its context within a particular program statement. To illustrate the type system, we give the language declarations that would be required for the program in Figure 1. BASE Name. CONSTANT Tom, Jerry : Name. PREDICATE Chase : Name * Name; Cat, Mouse : Name. Note that the declaration beginning BASE indicates that Name is a base type. In the statement Chase(x,y) ! Cat(x) & Mouse(y). the variables x and y are inferred to be of type Name. Polymorphic types can also be defined in Godel. They are constructed from the base types, type variables called parameters, and type constructors. Each constructor has an arity 1 attached to it. As an...
Redundant Argument Filtering of Logic Programs
 Logic Program Synthesis and Transformation. Proceedings of LOPSTR’96, LNCS 1207
, 1996
"... This paper is concerned with the problem of removing, from a given logic program, redundant arguments. These are arguments which can be removed without affecting correctness. Most program specialisation techniques, even though they perform argument filtering and redundant clause removal, fail to re ..."
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Cited by 42 (17 self)
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This paper is concerned with the problem of removing, from a given logic program, redundant arguments. These are arguments which can be removed without affecting correctness. Most program specialisation techniques, even though they perform argument filtering and redundant clause removal, fail to remove a substantial number of redundant arguments, yielding in some cases rather inefficient residual programs. We formalise the notion of a redundant argument and show that one cannot decide effectively whether a given argument is redundant. We then give a safe, effective approximation of the notion of a redundant argument and describe several simple and efficient algorithms calculating based on the approximative notion. We conduct extensive experiments with our algorithms on mechanically generated programs illustrating the practical benefits of our approach.
Conjunctive Partial Deduction: Foundations, Control, Algorithms, and Experiments
 J. LOGIC PROGRAMMING
, 1999
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