N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, October 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....Forschung under grant P9426 PHY. Financial support for the Austrian Research Institute for Artificial Intelligence is provided by the Austrian Federal Ministry for Science and Research. We include a collection of examples that has been distributed with the Monash University version of clp(R) Heintze et al. 87] and its inclusion into this distribution was kindly permitted by Roland Yap. 32.2 Solver Interface Until rational numbers become first class citizens in SICStus Prolog, rational arithmetics has to be emulated. Because of the emulation it is too expensive to support arithmetics with automatic ....

....stage of expansion, and so on. We recommend that you only turn on expansion temporarily while consulting or compiling files needing expansion with expand 0 and noexpand 0. 32.7. 1 Monash Examples This collection of examples has been distributed with the Monash University Version of clp(R) Heintze et al. 87] and its inclusion into this distribution was kindly permitted by Roland Yap. In order to execute the examples, a small compatibility package has to be loaded first: clp(r) use module(library( clpqr monash ) Then, assuming you are using clp(R) clp(r) expand, ....

N. Heintze, J. Ja#ar, S. Michaylov, P. Stuckey, R. Yap, The CLP(R) Programmers Manual, Monash University, Clayton, Victoria, Australia, Department of Computer Science, 1987.

....and interaction, that work does not have an exact characterization of the total number of iterations needed. The nite domains described in this work make a complete complexity analysis easy. Regular tree grammar based program analysis can be reformulated as setconstraint based analysis [21,22,9], but we do not know any work that treats precise and ecient dead code analysis for recursive data as we do. Melski and Reps [40,41] show the interconvertibility of a class of set constraints and context free language reachability and, at the end of [41] they show how general CFL reachability can ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, Oct. 1992.

.... results for program improvement [33] Finite transformers can be obtained by restricting them to be written in a specific meta language [14] This meta language corresponds to a restricted class of regular tree grammars extended with selectors [26, 14] and can be rewritten as a set of constraints [21, 22, 14]. This is essentially a masking of the explicit use of an approximation operation, called widening, when defining transformers [14] Approximation operations provide a more general solution and make the analysis framework more modular and flexible. We describe three efficient approximation ....

....operations. We combine carefully designed approximation operations to produce significantly more precise analysis results than previous methods. Such operations are difficult to design. While regular tree grammar based program analysis can be reformulated as set constraint based analysis [21, 22, 14], we do not know any work that treats precise and efficient dependence analysis for recursive data as we do. The overall goal is to analyze dead data and eliminate computations on them across recursions and loops, possibly interleaved with wrappers like classes in object oriented programming ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, Oct. 1992.

....of the total number of iterations needed. The finite domains described in this work make a complete analysis easy, and it yields a most precise liveness pattern for the data at each program point. Regular tree grammar based program analysis can be reformulated as setconstraint based analysis [18, 19, 9], but we do not know any work that treats precise and efficient dead code analysis for recursive data as we do. Melski and Reps [35, 36] show the interconvertibility of a class of set constraints and context free language reachability and, at the end of [35] they show how general CFL reachability ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, Oct. 1992.

....[1] that solving systems of such constraints is NEXPTIME complete. Our main contributions are to show that in practice, systems of constraints can be solved fairly efficiently, and that the hypergraph representation used in [1, 7] is in fact as practical for implementations as other techniques [2, 5, 6]. In order to gain this efficiency, we developed an algorithm for conjoining new constraints to a pre existing constraint system without doing the expensive cross product like operation suggested in [7] In addition, we describe two other methods to increase efficiency that may be of interest in ....

N. Heintze. Set Based Program Analysis. PhD dissertation, Carnegie Mellon University, Department of Computer Science, October 1992.

....of the total number of iterations needed. The finite domains described in this work make a complete analysis possible, yet still give significantly more precise analysis results than previous methods. Regular tree grammar based program analysis can be reformulated as set constraint based analysis [17, 18, 9], but we do not know any work that treats precise and efficient dead code analysis for recursive data as we do. The method and algorithms studied here have many applications: program slicing and specialization [51, 40] strength reduction, finite differencing, and incrementalization [7, 36, 31, ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, Oct. 1992.

....Forschung under grant P9426 PHY. Financial support for the Austrian Research Institute for Artificial Intelligence is provided by the Austrian Federal Ministry for Science and Research. We include a collection of examples that has been distributed with the Monash University version of clp(R) Heintze et al. 87] and its inclusion into this distribution was kindly permitted by Roland Yap. Constraint Logic Programming over Rationals or Reals 2 Solver Interface Until rational numbers become first class citizens in SICStus Prolog, rational arithmetics has to be emulated. Because of the emulation it is ....

....to another stage of expansion, and so on. We recommend that you only turn on expansion temporarily while consulting or compiling files needing expansion with expand 0 and noexpand 0. Monash Examples This collection of examples has been distributed with the Monash University Version of clp(R) Heintze et al. 87] and its inclusion into this distribution was kindly permitted by Roland Yap. In order to execute the examples, a small compatibility package has to be loaded first: clp(r) usemodule(library( clpqr monash ) Constraint Logic Programming over Rationals or Reals 19 Then, assuming you are ....

Heintze N., Jaffar J., Michaylov S., Stuckey P., Yap R.: The CLP(R) Programmers Manual, Monash University, Clayton, Victoria, Australia, Department of Computer Science, 1987.

....between these new systems is made clear, formalizing the description in [SH97] The differences between the two algorithms are expressed in a minimal fashion as a choice between inclusion and equality constraints. Our type systems are designed using term and set constraints. Set constraints [AW92, AW93, FA96, HJ90, Hei92] define inclusion relationships between types; we use set constraints to describe Andersen s analysis. Term constraints define equality relationships between types (e.g. ML type inference [Mil78] we use term equations to describe Steensgaard s analysis. We have implemented these new type systems ....

....in [AW93, FA97] Figure 3c gives two general rules that apply to all sorts. The first rule expresses that is transitive. The second flips constraints that arise from contravariant constructor arguments. 4 Andersen s Analysis: A First Cut We begin by examining why standard set based analysis [Hei92] seems insufficient for expressing Andersen s algorithm. Consider the C fragment e : x j e j e j e1 = e2 j e1 ; e2 consisting of variables, pointer dereferencing, the address of operator, assignment, and sequencing. Our goal is to assign a type and a series of constraints to each expression ....

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N. Heintze. Set Based Program Analysis. PhD dissertation, Carnegie Mellon University, Department of Computer Science, October 1992.

....of the total number of iterations needed. The finite domains described in this work make a complete analysis easy, yet still give significantly more precise analysis results than previous methods. Regular tree grammar based program analysis can be reformulated as set constraint based analysis [18, 19, 9], but we do not know any work that treats precise and efficient dead code analysis for recursive data as we do. The method and algorithms for dead code elimination studied here have many applications: program slicing and specialization [59, 44] strength reduction, finite differencing, and ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, Oct. 1992.

....or using approximation operations. Finite transformers can be obtained by restricting them to be written in a specific meta language [12] This meta language corresponds to a restricted class of regular tree grammars extended with selectors [20, 12] and can be rewritten as a set of constraints [16, 17, 12]. As discussed by Cousot and Cousot, this is essentially a masking of the explicit use of an approximation, called widening, when defining transformers [12] Appropriate finite abstract domains can often be obtained for various applications of the analysis, and they can provide sufficiently ....

....analysis result. Such operations are difficult to design, e.g. we found that the so called widening operation given in a previous work [12] may still lead to an infinitely increasing chain. While regular tree grammar based program analysis can be reformulated as setconstraint based analysis [16, 17, 12], we do not know any work that treats precise dead code analysis as we do. To conclude, the overall goal is to analyze dead data and eliminate computations on them across recursions and loops, possibly interleaved with wrappers like classes in object oriented programming styles. This paper ....

N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, October 1992.

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Heintze N., Ja#ar J., Michaylov S., Stuckey P., Yap R.: The CLP(R) Programmers Manual, Monash University, Clayton, Victoria, Australia, Department of Computer Science, 1987.

.... of tries for storing sets of keys that may contain prefixing keys (that is, keys that are prefixes of other keys in the set) was taken up by Knott in [Kno86] The first analysis of tries that store prefixing keys was done in [dlT87] under the prefix model which generalizes Trabb Pardo s model [Tra78] and is defined as follows. Definition 1.1 Prefix Model. The prefix model P(h; n; m) assumes as equally likely all sets of n strings with length at most h over an alphabet A of m characters. That is, all n elements subsets of A 0 [ A 1 [ A h . In this paper, we present an algebraic ....

....al. in [FRS85] for other models. As the main application of this approach, we analyzed the average running time of two algorithms for computing intersections of sets of binary strings under the set intersection prefix model (defined in x4) which generalizes Trabb Pardo s set intersection model [Tra78]. Section x2 introduces the root function method a uniform approach to deriving the expectations of a wide class of random variables under the prefix model. Section x3 drives the generating function translation rules corresponding to the prefix model. Section x4 illustrates the use of these ....

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L. I. Trabb Pardo. Set representation and set intersection. Ph.D. Thesis STAN--CS-- 78--681, Department of Computer Science, Stanford University, 1978.

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N. Heintze. Set-Based Program Analysis. PhD thesis, Department of Computer Science, Carnegie Mellon University, October 1992.

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N. Heintze. Set Based Program Analysis. PhD dissertation, Carnegie Mellon University, Department of Computer Science, Oct. 1992.

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N. Heintze, J. Jaffar, S. Michaylov, P. Stuckey, R. Yap, The CLP(R) Programmers Manual, Monash University, Clayton, Victoria, Australia, Department of Computer Science, 1987.

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Nevin Heintze. Set Based Program Analysis. PhD dissertation, Carnegie Mellon University, Department of Computer Science, October 1992. 28

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