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35
Solving ShapeAnalysis Problems in Languages with Destructive Updating
 POPL '96
, 1996
"... This paper concerns the static analysis of programs that perform destructive updating on heapallocated storage. We give an algorithm that conservatively solves this problem by using a finite shapegraph to approximate the possible “shapes” that heapallocated structures in a program can take on. In ..."
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Cited by 292 (19 self)
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This paper concerns the static analysis of programs that perform destructive updating on heapallocated storage. We give an algorithm that conservatively solves this problem by using a finite shapegraph to approximate the possible “shapes” that heapallocated structures in a program can take on. In contrast with previous work, our method M even accurate for certain programs that update cyclic data structures. For example, our method can determine that when the input to a program that searches a list and splices in a new element is a possibly circular list, the output is a possibly circular list.
Typedirected partial evaluation
 Proceedings of the TwentyThird Annual ACM Symposium on Principles of Programming Languages
, 1996
"... Abstract. Typedirected partial evaluation stems from the residualization of arbitrary static values in dynamic contexts, given their type. Its algorithm coincides with the one for coercing asubtype value into a supertype value, which itself coincides with the one of normalization in thecalculus. T ..."
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Cited by 207 (39 self)
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Abstract. Typedirected partial evaluation stems from the residualization of arbitrary static values in dynamic contexts, given their type. Its algorithm coincides with the one for coercing asubtype value into a supertype value, which itself coincides with the one of normalization in thecalculus. Typedirected partial evaluation is thus used to specialize compiled, closed programs, given their type. Since Similix, letinsertion is a cornerstone of partial evaluators for callbyvalue procedural programs with computational e ects. It prevents the duplication of residual computations, and more generally maintains the order of dynamic side e ects in residual programs. This article describes the extension of typedirected partial evaluation to insert residual let expressions. This extension requires the userto annotate arrowtypes with e ect information. It is achieved by delimiting and abstracting control, comparably to continuationbased specialization in direct style. It enables typedirected partial evaluation of e ectful programs (e.g.,ade nitional lambdainterpreter for an imperative language) that are in direct style. The residual programs are in Anormal form. 1
Efficient Type Inference for HigherOrder BindingTime Analysis
 In Functional Programming and Computer Architecture
, 1991
"... Bindingtime analysis determines when variables and expressions in a program can be bound to their values, distinguishing between early (compiletime) and late (runtime) binding. Bindingtime information can be used by compilers to produce more efficient target programs by partially evaluating prog ..."
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Cited by 91 (4 self)
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Bindingtime analysis determines when variables and expressions in a program can be bound to their values, distinguishing between early (compiletime) and late (runtime) binding. Bindingtime information can be used by compilers to produce more efficient target programs by partially evaluating programs at compiletime. Bindingtime analysis has been formulated in abstract interpretation contexts and more recently in a typetheoretic setting. In a typetheoretic setting bindingtime analysis is a type inference problem: the problem of inferring a completion of a λterm e with bindingtime annotations such that e satisfies the typing rules. Nielson and Nielson and Schmidt have shown that every simply typed λterm has a unique completion ê that minimizes late binding in TML, a monomorphic type system with explicit bindingtime annotations, and they present exponential time algorithms for computing such minimal completions. 1 Gomard proves the same results for a variant of his twolevel λcalculus without a socalled “lifting ” rule. He presents another algorithm for inferring completions in this somewhat restricted type system and states that it can be implemented in time O(n 3). He conjectures that the completions computed are minimal.
Occam's Razor in Metacomputation: the Notion of a Perfect Process Tree
, 1993
"... We introduce the notion of a perfect process tree as a model for the
full propagation of in forma tion in metacomputation. Starting with constant
propagation we construct stepbystep the driving mechanism used in supercompilation
which ensures the perfect propagation of information. The concept
of ..."
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Cited by 64 (14 self)
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We introduce the notion of a perfect process tree as a model for the
full propagation of in forma tion in metacomputation. Starting with constant
propagation we construct stepbystep the driving mechanism used in supercompilation
which ensures the perfect propagation of information. The concept
of a simple supercompiler based on perfect driving coupled with a simple
folding strategy is explained. As an example we demonstrate that specializing a
naive pattern matcher with respect to a fixed pattern obtains the efficiency of a
matcher generated by the Knuth, Morris & Pratt al gorithm.
Efficient Multilevel Generating Extensions for Program Specialization
, 1995
"... . Multiple program specialization can stage a computation into several computation phases. This paper presents an effective solution for multiple program specialization by generalizing conventional offline partial evaluation and integrating the "cogen approach" with a multilevel bindingtime analy ..."
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Cited by 59 (5 self)
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. Multiple program specialization can stage a computation into several computation phases. This paper presents an effective solution for multiple program specialization by generalizing conventional offline partial evaluation and integrating the "cogen approach" with a multilevel bindingtime analysis. This novel "multicogen approach" solves two fundamental problems of selfapplicable partial evaluation: the generationtime problem and the generatorsize problem. The multilevel program generator has been implemented for a higherorder subset of Scheme. Experimental results show a remarkable reduction of generation time and generator size compared to previous attempts of multiple selfapplication. 1 Introduction Stages of computation arise naturally in many programs, depending on the availability of data or the frequency with which the input changes. Code for later stages can be optimized based on values available in earlier stages. Partial evaluation has received much attention beca...
For a Better Support of Static Data Flow
 Functional Programming Languages and Computer Architecture
"... . This paper identifies and solves a class of problems that arise in binding time analysis and more generally in partial evaluation of programs: the approximation and loss of static information due to dynamic expressions with static subexpressions. Solving this class of problems yields substantial b ..."
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Cited by 59 (16 self)
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. This paper identifies and solves a class of problems that arise in binding time analysis and more generally in partial evaluation of programs: the approximation and loss of static information due to dynamic expressions with static subexpressions. Solving this class of problems yields substantial binding time improvements and thus dramatically better results not only in the case of partial evaluation but also for static analyses of programs  this last point actually is related to a theoretical result obtained by Nielson. Our work can also be interpreted as providing a solution to the problem of conditionally static data, the dual of partially static data. We point out which changes in the control flow of a source program may improve its static data flow. Unfortunately they require one to iterate earlier phases of partial evaluation. We show how these changes are subsumed by transforming the source program into continuationpassing style (CPS). The transformed programs get specializ...
Program specialization via program slicing
 Proceedings of the Dagstuhl Seminar on Partial Evaluation, volume 1110 of Lecture Notes in Computer Science
, 1996
"... This paper concerns the use of program slicing to perform a certain kind of programspecialization operation. The specialization operation that slicing performs is different from the specialization operations performed by algorithms for partial evaluation, supercompilation, bifurcation, and deforest ..."
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Cited by 55 (4 self)
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This paper concerns the use of program slicing to perform a certain kind of programspecialization operation. The specialization operation that slicing performs is different from the specialization operations performed by algorithms for partial evaluation, supercompilation, bifurcation, and deforestation. In particular, we present an example in which the specialized program that we create via slicing could not be created as the result of applying partial evaluation, supercompilation, bifurcation, or deforestation to the original unspecialized program. Specialization via slicing also possesses an interesting property that partial evaluation, supercompilation, and bifurcation do not possess: The latter operations are somewhat limited in the sense that they support tailoring of existing software only according to the ways in which parameters of functions and procedures are used in a program. Because parameters to functions and procedures represent the range of usage patterns that the designer of a piece of software has anticipated, partial evaluation, supercompilation, and bifurcation support specialization only in ways that have already been “foreseen ” by the software’s author. In contrast, the specialization operation that slicing supports permits programs to be specialized in ways
Deriving incremental programs
, 1993
"... A systematic approach i s g i v en for deriving incremental programs from nonincremental programs written in a standard functional programming language. We exploit a number of program analysis and transformation techniques and domainspeci c knowledge, centered around e ective utilization of cachin ..."
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Cited by 39 (21 self)
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A systematic approach i s g i v en for deriving incremental programs from nonincremental programs written in a standard functional programming language. We exploit a number of program analysis and transformation techniques and domainspeci c knowledge, centered around e ective utilization of caching, in order to provide a degree of incrementality not otherwise achievable by a generic incremental evaluator. 1
Binding Time Analysis: A New PERspective
 In Proceedings of the ACM Symposium on Partial Evaluation and SemanticsBased Program Manipulation (PEPM'91
, 1991
"... Given a description of the parameters in a program that will be known at partial evaluation time, a binding time analysis must determine which parts of the program are dependent solely on these known parts (and therefore also known at partial evaluation time). In this paper a binding time analysis f ..."
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Cited by 33 (5 self)
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Given a description of the parameters in a program that will be known at partial evaluation time, a binding time analysis must determine which parts of the program are dependent solely on these known parts (and therefore also known at partial evaluation time). In this paper a binding time analysis for the simply typed lambda calculus is presented. The analysis takes the form of an abstract interpretation and uses a novel formalisation of the problem of binding time analysis, based on the use of partial equivalence relations. A simple proof of correctness is achieved by the use of logical relations. 1 Introduction Given a description of the parameters in a program that will be known at partial evaluation time, a binding time analysis must determine which parts of the program are dependent solely on these known parts (and therefore also known at partial evaluation time). A binding time analysis performed prior to the partial evaluation process can have several practical benefits (see [...
What Not to Do When Writing an Interpreter for Specialisation
 In Danvy et al
, 1996
"... . A partial evaluator, given a program and a known "static" part of its input data, outputs a specialised or residual program in which computations depending only on the static data have been performed in advance. Ideally the partial evaluator would be a "black box" able to extract nontrivial stati ..."
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Cited by 29 (3 self)
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. A partial evaluator, given a program and a known "static" part of its input data, outputs a specialised or residual program in which computations depending only on the static data have been performed in advance. Ideally the partial evaluator would be a "black box" able to extract nontrivial static computations whenever possible; which never fails to terminate; and which always produces residual programs of reasonable size and maximal efficiency, so all possible static computations have been done. Practically speaking, partial evaluators often fall short of this goal; they sometimes loop, sometimes pessimise, and can explode code size. A partial evaluator is analogous to a spirited horse: while impressive results can be obtained when used well, the user must know what he/she is doing. Our thesis is that this knowledge can be communicated to new users of these tools. This paper presents a series of examples, concentrating on a quite broad and on the whole quite successful application ...