Controlling generalization and polyvariance in partial deduction of normal logic programs
Open accessAbstract
Given a program and some input data, partial deduction computes a specialized program handling any remaining input more efficiently. However, controlling the process well is a rather difficult problem. In this article, we elaborate global control for partial deduction: for which atoms, among possibly infinitely many, should specialized relations be produced, meanwhile guaranteeing correctness as well as termination? Our work is based on two ingredients. First, we use the concept of a characteristic tree, encapsulating specialization behavior rather than syntactic structure, to guide generalization and polyvariance, and we show how this can be done in a correct and elegant way. Second, we structure combinations of atoms and associated characteristic trees in global trees registering “causal” relationships among such pairs. This allows us to spot looming nontermination and perform proper generalization in order to avert the danger, without having to impose a depth bound on characteristic trees. The practical relevance and benefits of the work are illustrated through extensive experiments. Finally, a similar approach may improve upon current (on-line) control strategies for program transformation in general such as (positive) supercompilation of functional programs. It also seems valuable in the context of abstract interpretation to handle infinite domains of infinite height with more precision.
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TL;DR
The paper develops global control for partial deduction of normal logic programs using characteristic trees and characteristic atoms, preserving specialization behavior during generalization and removing ad hoc depth bounds via global trees. It proves correctness and termination for the resulting algorithms and reports experiments with the ECCE system showing improved speedups and code size over prior partial-deduction systems.
Key findings
- The tree-based Algorithm 4.6.1 always terminates and outputs a P-covered set of characteristic atoms; correctness then follows from Theorem 3.3.2.
- Removing the depth bound improved ECCE results: ECCE-x-10 had total speedup 2.13, weighted speedup 2.23, code size 224.35 KB, and total transformation time 112.72 min; ECCE-x had total speedup 2.51, weighted speedup 2.75, code size 135.91 KB, and total transformation time 2.70 min.
- ECCE-based systems terminated on all examples, while MIXTUS, PADDY, and SP did not properly terminate for at least one benchmark each.
- The paper reports that getting rid of the depth bound increased total speedup from 2.13 to 2.51 and weighted speedup from 2.23 to 2.75, while decreasing specialized code size and drastically reducing transformation time.
Methods
- Theoretical framework for partial deduction of normal logic programs: characteristic paths/trees, characteristic atoms, concretizations, resultants, renaming, and correctness results for partial deduction with characteristic atoms.
- Algorithms: Algorithm 3.4.3 for ecological partial deduction using chmsg to preserve characteristic trees; Algorithm 4.6.1 for global tree-based partial deduction using characteristic atoms and the well-quasi relation ¢*ca; plus postprocessing to remove superfluous polyvariance.
- Experiments with the ECCE implementation on a benchmark suite, comparing ECCE-d, ECCE-x-10, ECCE-x, MIXTUS, PADDY, and SP using relative run-times, code size, and transformation times.
Limitations
- The paper states that local control issues remain open, especially fully automatic satisfactory unfolding of metainterpreters and good treatment of truly nondeterminate programs; specialization quality depends heavily on the local control used.
- The paper notes that the global control method may have considerable complexity: checking ¢*ca is costly, and maintaining a well-quasi-ordering entails searching and repeated comparisons with ancestors; the prototype was not tuned for transformation speed.
- The paper states that built-ins require adaptations, constructive negation was not incorporated, and dynamic constants/functors are treated like variables; postprocessing is needed to remove superfluous polyvariance.
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Claims the paper makes
13 of 85 cited sources checked · 8 supported · 0 flagged · accuracy not yet measured
- Interpretationreasoning
Blending the general framework in Martens and Gallagher [1995] with the framework developed in Section 3 yields an apparatus for on-line global control of partial deduction.
“In Section 4 we then solve the second problem, blending the general framework in Martens and Gallagher [1995] with the framework developed in Section 3. We thus obtain an elegant, sophisticated, and precise apparatus for on-line global control of partial deduction.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Martens and Gallagher [1995] source
- Interpretationcitation
The method for partial deduction described in Section 3, using the framework of Section 3, guarantees preservation of characteristic trees.
“The method for partial deduction as described in this section, using the framework of Section 3, has been called ecological partial deduction by Leuschel [1995] because it guarantees the preservation of characteristic trees.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Leuschel [1995] source
The copy discusses partial evaluation of a meta-interpreter for integrity checking, including unfolding it in Section 4, but does not address preservation of characteristic trees. Searches for “ecological partial deduction” and “characteristic trees” found no passage stating the claimed name or guarantee. The indexed passages provide no page numbers. (LLM, conf=0.76)
Experimental — accuracy not yet measured
- Interpretationcitation
Importing and adapting m-trees of Martens and Gallagher [1995] overcomes the need for a depth bound on characteristic trees to guarantee termination of partial deduction.
“Importing and adapting m-trees of Martens and Gallagher [1995], we have overcome the need for a depth bound on characteristic trees to guarantee termination of partial deduction.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Martens and Gallagher [1995] source
- Premisecitation
If A and B are expressions such that B is strictly more general than A, then h(A) > h(B).
“Lemma C.2. If A and B are expressions such that B is strictly more general than A, then h(A) > h(B).”
Quote in the paperSubstantial claim1 of 2 sources checked- cites Gallagher and Bruynooghe [1990]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martens and Gallagher [1995] source
Lemma 3.23 states the inequality for atoms: if B is strictly more general than A, then h(A) > h(B). The citing sentence broadens “atoms” to “expressions,” which the lemma does not establish. The supplied copy gives no page number for the lemma. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingreasoning
Let à be a set of P-characteristic atoms. Then ¢*ca is a well-quasi relation on Ã.
“Proposition 4.4.11.Let à be a set of P -characteristic atoms.Then ¢ * ca is a well-quasi relation on Ã.”
- Also stated in: § Induction Step: · plain
“Proposition 4.4.11.Let à be a set of P -characteristic atoms.Then ¢ * ca is a well-quasi relation on Ã.”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Higman [1952] source
- cites Kruskal [1960] source
Section 2 defines well-quasi-ordering, and the paper discusses well-quasi-ordered tree spaces, but these passages do not address P-characteristic atoms or the relation ¢*ca. Searches for “P-characteristic atoms” and the claimed relation found no passage establishing that proposition; page numbers were not available in our copy. (LLM, conf=0.72)
Experimental — accuracy not yet measured - cites Dershowitz and Jouannaud [1990] source
- Also stated in: § Induction Step: · plain
- Findingown data
In Example 4.1.1, unfolding, including determinate and well-founded unfolding, produces an infinite number of different characteristic atoms, all with a different characteristic tree.
“As can be noticed in Figure 4, unfolding (determinate [Gallagher 1991;Gallagher Bruynooghe [1991]; Leuschel and De Schreye 1998] and well founded [Bruynooghe et al. 1992;Martens and De Schreye 1996;Martens et al. 1994], among others) produces an infinite number of different characteristic atoms, all with a different characteristic tree.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Gallagher 1991 source
- cites Gallagher Bruynooghe [1991]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Leuschel and De Schreye 1998
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingreasoning
Because the concretizations in P of the elements in à are disjoint, there exists only one renaming function ρα based on α.
“Because the concretizations in P of the elements in à are disjoint there exists only one renaming function ρ α based on α.”
Quote in the paperNot a substantial claim - Findingreasoning
Algorithm 4.6.1 always terminates.
“Theorem 4.6.2.Algorithm 4.6.1 always terminates.”
- Also stated in: § 4.6 A Tree-Based Algorithm · boosted
“We have thus established termination of Algorithm 4.6.1.”
Quote in the paperSubstantial claim - Also stated in: § 4.6 A Tree-Based Algorithm · boosted
- Findingnone given
The set of characteristic atoms output by Algorithm 4.6.1 is P-covered.
“Theorem 4.6.3.Let P be a program, input to Algorithm 4.6.1, and let à be the corresponding set of characteristic atoms produced as output.Then à is P -covered.”
Quote in the paperSubstantial claim - Findingown data
ECCE-x achieved a weighted speedup of 2.75.
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Quote in the paperSubstantial claim - Findingown data
ECCE-d achieved a total speedup of 1.90.
“ECCE-d 1.90 2.16 0.85 2.57 1.74”
Quote in the paperNot a substantial claim - Findingown data
ECCE-x achieved a Not FU speedup of 2.02.
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Quote in the paperNot a substantial claim - Findingown data
SP achieved a total speedup of 1.46.
“SP 1.46 1.56 0.86 2.08 1.32”
Quote in the paperNot a substantial claim - Findingown data
ECCE-x achieved a total speedup of 2.51.
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Quote in the paperSubstantial claim - Findingown data
ECCE-x-10 achieved a total speedup of 2.13.
“ECCE-x-10 2.13 2.23 0.79 7.07 1.71”
Quote in the paperNot a substantial claim - Findingown data
The existing systems MIXTUS, PADDY and SP did not properly terminate for at least one benchmark each.
“all the existing systems, MIXTUS, PADDY and SP, did not (properly) terminate for at least one benchmark each.”
Quote in the paperNot a substantial claim - Findingown data
ECCE-x-10 has a better total speedup than earlier systems.
“even the system ECCE-x-10 has a better total speedup than earlier systems.”
Quote in the paperNot a substantial claim - Findingown data
ECCE-x achieved a FU speedup of 8.36.
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Quote in the paperNot a substantial claim - Findingown data
For benchmarks model elim.app, liftsolve.app, and liftsolve.db1, which exhibit interpretation overhead, ECCE-x obtains speedup factors of about 8, 17, and 50 respectively.
“for the benchmarks model elim.app,liftsolve.app,and liftsolve.db1-whichexhibit interpretation overhead-ECCE-x obtains speedup factors of about 8, 17, and 50 respectively.”
Quote in the paperSubstantial claim - Findingown data
ECCE-x achieved a worst speedup of 0.92.
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Quote in the paperNot a substantial claim - Findingown data
PADDY achieved a total speedup of 2.08.
“PADDY 2.08 2.31 0.68 8.12 1.65”
Quote in the paperNot a substantial claim - Findingreasoning
The set of dynamic constants and functors is possibly infinite.
“The set of dynamic constants and functors is possibly infinite”
Quote in the paperSubstantial claim - Findingown data
MIXTUS achieved a total speedup of 2.08.
“MIXTUS 2.08 2.48 0.65 8.13 1.65”
Quote in the paperNot a substantial claim - Findingreasoning
The ECCE-based systems terminated on all examples.
“The ECCE-based systems did terminate on all examples, as would be expected by the results presented earlier in the article.”
Quote in the paperSubstantial claim - Findingnone given
The worst-case slowdown is only 8%.
“the worst-case slowdown of only 8%”
Quote in the paperSubstantial claim - Findingreasoning
Let τ_A and τ_B be two nonempty characteristic trees. Then the output τ of Algorithm 4.3.6 is the unique most specific generalization of τ_A and τ_B.
“Proposition 4.3.9.Let τ A , τ B be two nonempty characteristic trees.Then the output τ of Algorithm 4.3.6 is the (unique) most specific generalization of τ A and τ B .”
Quote in the paperSubstantial claim - Findingreasoning
If (A, τ) is a safe P-characteristic atom, then there exists an unfolding rule U such that τ ⊆ chtree(← A, P, U).
“Lemma B.2.9.Let τ be a characteristic tree, P a program and (A, τ ) a Pcharacteristic atom.If (A, τ ) is safe then there exists an unfolding rule such that τ ⊆ chtree(← A, P, U ).”
Quote in the paperSubstantial claim - Findingreasoning
Let V be a WQR on V and σ = v1, v2, ... an infinite sequence of elements of V. There exists an i > 0 such that the set {v_j | i < j ∧ v_i V v_j} is infinite.
“Lemma F.2. Let V be a WQR on V and let σ = v 1 , v 2 , . . .be an infinite sequence of elements of V . (1 ) There exists an i > 0 such that the set {v j | i < j ∧ v i V v j } is infinite.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The axiom of choice holds.
- Findingnone given
Let P be a normal program and G a normal goal. If P ∪ {G} has a finitely failed SLDNF-tree of height h and there is an SLDNF-derivation from G to G1, then P ∪ {G1} has a finitely failed SLDNF-tree of height ≤ h.
“Lemma B.2.10(Persistence of Failure).Let P be a normal program and G a normal goal.If P ∪ {G} has a finitely failed SLDNF-tree of height h and there is an SLDNF-derivation from G to G 1 , then P ∪{G 1 } has a finitely failed SLDNF-tree of height ≤ h.”
Quote in the paperSubstantial claim - Findingreasoning
Under the conditions of Theorem B.2.12, P ∪ {ρα(G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.
“(2 ) P ∪ {ρ α (G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Findingreasoning
Let <_V be a well-founded order on V. Then the relation V defined by v1 V v2 iff v1 >_V v2 is a WQR on V.
“Lemma F.1 (WQR from WFO).Let < V be a well-founded order on V .Then V , defined by v 1 V v 2 if and only if v 1 > V v 2 , is a WQR on V .”
Quote in the paperSubstantial claim - Findingreasoning
¢* can be expressed as a combination of two relations on expressions: ¢ and NotStrictInst, where A NotStrictInst B if and only if B ≺ A (i.e., B is not strictly more general than A or equivalently A is not a strict instance of B).
“¢ * can be expressed as a combination of two relations on expressions: ¢ and N otStrictInst where A N otStrictInst B if and only if B ≺ A (i.e., B is not strictly more general than A or equivalently A is not a strict instance of B).”
Quote in the paperSubstantial claim - Findingreasoning
Let V be a WQR on V and σ = v1, v2, ... an infinite sequence of elements of V. There exists an infinite subsequence σ* = v*1, v*2, ... of σ such that for all i < j we have v*_i V v*_j.
“(2 ) There exists an infinite subsequence σ * = v * 1 , v * 2 , . . . of σ such that for all i < j we have v * i V v * j .”
Quote in the paperSubstantial claim- The authors state this as an assumption: The axiom of choice holds.
- Findingreasoning
Let τ1 and τ2 be two characteristic trees and let δ ∈ prefix(τ1) be a characteristic path. If τ1 τ τ2 then τ1↓δ τ τ2↓δ.
“Lemma G.1.Let τ 1 and τ 2 be two characteristic trees and let δ ∈ prefix (τ 1 ) be a characteristic path.If τ 1 τ τ 2 then τ 1 ↓ δ τ τ 2 ↓ δ.”
Quote in the paperSubstantial claim - Findingreasoning
¢* is a WQR on expressions over a finite alphabet.
“Hence we can apply Lemma F.3 to deduce that ¢ * is also a WQR on expressions over a finite alphabet.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lemma F.3
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingnone given
The relation ¢ is a WQO on the set of expressions over a finite alphabet.
“Proposition 4.4.4.The relation ¢ is a WQO on the set of expressions over a finite alphabet.”
Quote in the paperNot a substantial claim - Findingown data
The converse of Proposition 4.3.13 does not hold.
“The converse of the above proposition does of course not hold.”
Quote in the paperNot a substantial claim - Findingcitation
For any two characteristic trees τ1 and τ2, τ1 ≡τ τ2 if and only if τ1 = τ2.
“Lemma 4.3.3.Let τ 1 , τ 2 be two characteristic trees.Then τ 1 ≡ τ τ 2 if and only if τ 1 = τ 2 .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Appendix D
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingcitation
For any two characteristic atoms (A, τA) and (B, τB), if (A, τA) ca (B, τB) then γP(A, τA) ⊇ γP(B, τB).
“Proposition 4.3.13.Let (A, τ A ) and (B, τ B ) be two characteristic atoms.If (A, τ A ) ca (B, τ B ) then γ P (A, τ A ) ⊇ γ P (B, τ B ).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Appendix D
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingreasoning
chmsg() always generates more general characteristic atoms (any precise concretization of an atom in Ãi is a precise concretization of an atom in Ãi+1).
“Furthermore chmsg() always generates more general characteristic atoms (even in the sense that any precise concretization of an atom in Ãi is a precise concretization of an atom in Ãi+1 -this follows immediately from Definitions 3.1.3and 3.4.1).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Definitions 3.1.3
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites 3.4.1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingreasoning
Any τ_i arising during the execution of Algorithm 4.3.6 satisfies δ ∈ τ_i ⇒ δ ∈ prefix(τ_A) ∩ prefix(τ_B).
“Lemma E.1.Any τ i arising during the execution of Algorithm 4.3.6 satisfies the property that δ ∈ τ i ⇒ δ ∈ prefix (τ A ) ∩ prefix (τ B ).”
Quote in the paperSubstantial claim - Findingnone given
Let 1V and 2V be WQR's on V. Then the relation V defined by v1 V v2 if and only if v1 1V v2 and v1 2V v2, is also a WQR on V.
“Lemma F.3 (Combination of WQR). Let 1 V and 2 V be WQR's on V . Then the relation V defined by v 1 V v 2 if and only if v 1 1 V v 2 and v 1 2 V v 2 , is also a WQR on V .”
Quote in the paperNot a substantial claim - Findingreasoning
For any characteristic trees τ1, τ2, and τ3, if τ1 τ τ2 and τ2 τ τ3 then τ1 τ τ3.
“Lemma 4.3.4.Let τ 1 , τ 2 , and τ 3 be characteristic trees.If τ 1 τ τ 2 and τ 2 τ τ 3 then τ 1 τ τ 3 .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Definition 4.3.1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingreasoning
Let P be a normal program, G a goal, à a finite set of safe P-characteristic atoms and P the partial deduction of P with respect to à and some ρα. If à is P-covered and G is P-covered by Ã, then P ∪ {ρα(G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.
“Theorem B.2.12.Let P be a normal program, G a goal, à a finite set of safe P -characteristic atoms and P the partial deduction of P with respect to à and some ρ α .If à is P -covered and if G is P -covered by à then the following hold: (1 ) P ∪ {ρ α (G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Interpretationreasoning
This loss of precision leads to suboptimal specialized programs.
“This loss of precision leads to suboptimal specialized programs.”
Quote in the paperSubstantial claim - Interpretationreasoning
If Algorithm 3.4.3 generates a finite number of distinct characteristic trees, then it produces a partial deduction satisfying the requirements of Theorem 3.3.2 for any goal G whose atoms are instances of atoms in G.
“If Algorithm 3.4.3generates a finite number of distinct characteristic trees then it terminates and produces a partial deduction satisfying the requirements of Theorem 3.3.2for any goal G whose atoms are instances of atoms in G.”
Quote in the paperSubstantial claim - Interpretationreasoning
Renaming becomes even more compelling in partial deduction with characteristic atoms because the same atom A might occur in several characteristic atoms with different associated characteristic trees.
“As such, the same atom A might occur in several characteristic atoms, but with different associated characteristic trees.This means that renaming, as a way to ensure independence, becomes even more compelling than in the standard partial deduction setting.”
Quote in the paperSubstantial claim - Interpretationnone given
Imposing characteristic trees on generalized atoms preserves characteristic trees during abstraction.
“We now present a way to preserve characteristic trees during abstraction.The basic idea is to simply impose characteristic trees on the generalized atoms.”
Quote in the paperNot a substantial claim - Premisecitation
Under the conditions of closedness and independence stated in Lloyd and Shepherdson [1991], correctness of the specialized program is guaranteed.
“Under the conditions stated in Lloyd and Shepherdson [1991], namely closedness and independence, correctness of the specialized program is guaranteed.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lloyd and Shepherdson [1991] source
- Interpretationreasoning
In those cases Algorithm 3.4.3, as well as all earlier approaches based on characteristic trees, terminates at the cost of imposing an ad hoc depth bound on characteristic trees.
“In those cases Algorithm 3.4.3,as well as all earlier approaches based on characteristic trees [Gallagher 1991;Gallagher and Bruynooghe 1991;Leuschel and De Schreye 1998], terminates at the cost of imposing an ad hoc depth bound on characteristic trees.”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationreasoning
Structuring combinations of atoms and associated characteristic trees in global trees that register causal relationships allows the partial deduction process to spot looming nontermination and perform proper generalization without imposing a depth bound on characteristic trees.
“Second, we structure combinations of atoms and associated characteristic trees in global trees registering “causal” relationships among such pairs.This allows us to spot looming nontermination and perform proper generalization in order to avert the danger, without having to impose a depth bound on characteristic trees.”
Quote in the paperSubstantial claim - Premisecitation
Prior characteristic-tree approaches have always been limited by an ad hoc depth bound, possibly leading to very undesirable specialization results.
“Second, the characteristic trees have always been limited by some ad hoc depth bound, possibly leading to very undesirable specialization results (as we will show later in the article).”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationreasoning
Characteristic trees, which encapsulate specialization behavior rather than syntactic structure, can be used to guide generalization and polyvariance in partial deduction in a correct way.
“First, we use the concept of a characteristic tree, encapsulating specialization behavior rather than syntactic structure, to guide generalization and polyvariance, and we show how this can be done in a correct and elegant way.”
Quote in the paperSubstantial claim - Premisecitation
Losses of precision from failing to preserve characteristic trees can also lead to nontermination of the partial deduction process.
“As explained by Leuschel and De Schreye [1998], these losses of precision can also lead to nontermination of the partial deduction process, further illustrating the importance of preserving characteristic trees upon generalization.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Leuschel and De Schreye [1998]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationcitation
For a P-characteristic atom (A,τ), the derivations in D_P(A,τ) are necessarily finite and nonfailing.
“Note that the derivations in D P (A, τ ) are necessarily finite and nonfailing (because (A, τ ) is a P -characteristic atom; see also Lemma B.2.9, in the electronic appendix to this article).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lemma B.2.9
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationnone given
If the standard partial deduction algorithm terminates, then independence and coveredness are ensured.
“But if the above algorithm terminates then independence and coveredness are ensured.”
Quote in the paperSubstantial claim - Interpretationreasoning
If Algorithm 3.4.3 generates a finite number of distinct characteristic trees, then it terminates.
“If Algorithm 3.4.3generates a finite number of distinct characteristic trees then it terminates and produces a partial deduction satisfying the requirements of Theorem 3.3.2for any goal G whose atoms are instances of atoms in G.”
Quote in the paperSubstantial claim - Interpretationreasoning
Under the conditions of Theorem 3.3.2, P ∪ {ρα(G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.
“(2 ) P ∪ {ρ α (G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Interpretationnone given
For a fairly large class of realistic programs and unfolding rules, the number of different characteristic trees generated is infinite.
“However, it turns out that for a fairly large class of realistic programs (and unfolding rules), the number of different characteristic trees generated is infinite.”
Quote in the paperSubstantial claim - Interpretationreasoning
The control of polyvariance problem can be reformulated as finding an abstraction operator that maximizes specialization while ensuring termination.
“With this observation we can reformulate the control of polyvariance problem as one of finding an abstraction operator which maximizes specialization while ensuring termination.”
Quote in the paperSubstantial claim - Interpretationreasoning
Under the conditions of Theorem 3.3.2, P ∪ {ρα(G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.
“If à is P -covered and if G is P -covered by à then the following hold: (1 ) P ∪ {ρ α (G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Interpretationreasoning
Characteristic atoms provide a proper generalization of the way atoms are used in standard partial deduction.
“So, characteristic atoms along with Definition 3.1.3provide a proper generalization of the way atoms are used in the standard partial deduction approach.”
Quote in the paperSubstantial claim - Interpretationreasoning
There is no fundamental difference between the approach that throws away the original program and the Lloyd and Shepherdson framework; keeping part of the original program can be simulated by using unconstrained characteristic atoms of the form (A, {}) combined with a renaming α such that α((A, {})) = A.
“However, there is no fundamental difference between these two approaches: keeping part of the original program can be simulated in our approach by using unconstrained characteristic atoms of the form (A, { }) combined with a renaming α such that α((A, { })) = A.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lloyd and Shepherdson [1991] source
- Premisenone given
Prior approaches based on characteristic trees failed to preserve characteristic trees upon generalization: two atoms with identical specialization behavior may be generalized by one with a completely different specialization behavior.
“First, they failed to preserve the characteristic trees upon generalization: two atoms with identical specialization behavior may be generalized by one with a completely different specialization behavior.”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationnone given
The ecological partial deduction principle developed in Section 3 ensures the preservation of characteristic trees.
“After presenting some required background about partial deduction and characteristic trees in Section 2, we address the first problem in Section 3 by developing the ecological partial deduction principle, ensuring the preservation of characteristic trees.”
Quote in the paperSubstantial claim - Interpretationreasoning
An unconstrained characteristic atom in P is safe in P.
“An unconstrained characteristic atom in P is safe in P .6”
Quote in the paperSubstantial claim - Interpretationnone given
A function . satisfying Definition 4.4.8 exists.
“A function .satisfying Definition 4.4.8exists.”
Quote in the paperNot a substantial claim - Interpretationnone given
Characteristic trees encode the particular order in which literals are selected and thus do not take advantage of the independence of the computation rule.
“Indeed characteristic trees also encode the particular order in which literals are selected and thus do not take advantage of the independence of the computation rule.”
Quote in the paperNot a substantial claim - Interpretationnone given
The relation ¢* is a well-quasi relation on the set of expressions over a finite alphabet.
“The relation ¢ * is a well-quasi relation on the set of expressions over a finite alphabet.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The polyvariance-reducing postprocessing proposed in Section 4.8 avoids the phenomenon of losing subsequent instantiation at the global level.
“The polyvariance-reducing postprocessing that we propose in this section therefore avoids the latter phenomenon.”
Quote in the paperSubstantial claim - Interpretationnone given
Checking ¢ * ca on characteristic atoms is a costly operation that adds to the innate complexity of maintaining a well-quasi-ordering.
“Moreover, in our particular case, checking ¢ * ca on characteristic atoms is in itself a quite costly operation, adding to the innate complexity of maintaining a well-quasi-ordering.”
Quote in the paperNot a substantial claim - Interpretationnone given
For two nonempty characteristic trees τA and τB, the output τ of Algorithm 4.3.6 is the unique most specific generalization of τA and τB.
“Let τ A , τ B be two nonempty characteristic trees.Then the output τ of Algorithm 4.3.6 is the unique most specific generalization of τ A and τ B .”
Quote in the paperNot a substantial claim - Interpretationnone given
Unlike ecological partial deduction as presented in Section 3.4, Algorithm 4.6.1 will often output several characteristic atoms with the same characteristic tree, each giving rise to a different specialized version of the same original predicate definition.
“Unlike ecological partial deduction as presented in Section 3.4, Algorithm 4.6.1 will obviously often output several characteristic atoms with the same characteristic tree (each giving rise to a different specialized version of the same original predicate definition).”
Quote in the paperSubstantial claim - Interpretationown data
Only measuring growth of characteristic trees, even in a refined way, does not always lead to satisfactory specialization.
“Example 4.2.1 demonstrates that only measuring growth of characteristic trees, even in a refined way, does not always lead to satisfactory specialization.”
Quote in the paperSubstantial claim - Interpretationown data
The intuition that testing only homeomorphic embedding on the atom part is sufficient for deciding when to abstract in a global tree is incorrect.
“Nonetheless, the intuition turns out to be incorrect.”
- Also stated in: § 4.7 Further Discussion · plain
“A method based on testing only ¢ * on the atom component would abstract B unnecessarily.”
- Also stated in: § 4.7 Further Discussion · plain
“Again, A ¢ * B holds, but not τ A ¢ * τ B .”
Quote in the paperSubstantial claim - Also stated in: § 4.7 Further Discussion · plain
- Interpretationreasoning
A growing of a characteristic tree not coupled with a growing of the syntactic structure indicates a fake growing caused by a conservative unfolding rule.
“A growing of a characteristic tree not coupled with a growing of the syntactic structure then indicates a fake growing caused by a conservative unfolding rule.”
Quote in the paperSubstantial claim - Interpretationreasoning
If τ1 τ τ2 and chtree(G, P, U) = τ2, then for some U, chtree(G, P, U) = τ1.
“Let τ 1 and τ 2 be characteristic trees such that τ 1 τ τ 2 .If chtree(G, P, U ) = τ 2 then for some U , chtree(G, P, U ) = τ 1 .”
Quote in the paperSubstantial claim - Interpretationreasoning
Characteristic trees can carry too much information, in that different characteristic trees can represent the same local specialization behavior.
“Sometimes, however, characteristic trees carry too much information, in the sense that different characteristic trees can represent the same local specialization behavior.”
Quote in the paperNot a substantial claim - Interpretationreasoning
¢* is not a WQO because it is not transitive.
“Observe that ¢ * is not a WQO because it is not transitive.”
Quote in the paperSubstantial claim - Interpretationreasoning
Ensuring termination through a well-quasi relation or order is structurally much more costly than using a well-founded ordering.
“Indeed, first, ensuring termination through a well-quasi relation or order is structurally much more costly than the alternative of using a well-founded ordering.”
Quote in the paperNot a substantial claim - Interpretationcitation
The mapping developed in Appendix G has the property that the structure of a characteristic tree τ is reflected in the treestructure of the term τ, ensuring that the usefulness of ¢ for spotting nonterminating processes carries over to characteristic trees.
“The mapping developed in Appendix G is actually a good candidate, as it has the desirable property that the structure of a characteristic tree τ is reflected in the treestructure of the term τ , thus ensuring that the usefulness of ¢ for spotting nonterminating processes (e.g., see Marlet [1994]) carries over to characteristic trees.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Marlet [1994]
- Interpretationnone given
Generalizing atoms with identical characteristic trees might lead to the occurrence of more general atoms in the leaves of the associated local tree.
“The case of global precision is slightly more complicated: generalizing atoms with identical characteristic trees might lead to the occurrence of more general atoms in the leaves of the associated local tree.”
Quote in the paperNot a substantial claim - Interpretationreasoning
When using the ¢ relation instead of ¢ * , the algorithm could loop because M would not necessarily be more general than CA B.
“Note that, when using the ¢ relation instead of ¢ * , M would not necessarily be more general than CA B , i.e., the algorithm could loop.”
Quote in the paperSubstantial claim - Interpretationown data
The relation τ is not a WQR on characteristic trees, even in the context of a given fixed program P.
“Notice that the relation τ is not a WQR on characteristic trees, even in the context of a given fixed program P .”
Quote in the paperSubstantial claim - Interpretationreasoning
Generalizing atoms with identical characteristic trees might lose subsequent instantiation at the global level, possibly leading to a different and less precise set of characteristic atoms.
“In other words, we might loose subsequent instantiation at the global level, possibly leading to a different and less precise set of characteristic atoms.”
Quote in the paperSubstantial claim - Interpretationcitation
The specialization produced by Algorithm 4.6.1 is correct.
“The correctness of the specialization now follows from Theorem 3.3.2.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Theorem 3.3.2
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Algorithm 4.3.6 terminates.
“Algorithm 4.3.6 terminates and produces as output a characteristic tree τ such that if chtree(G, P, U ) = τ A (respectively τ B ), then for some U , chtree(G, P, U ) = τ .”
- Also stated in: § Induction Step: · plain
“Lemma 4.3.8.Algorithm 4.3.6 terminates and produces as output a characteristic tree τ such that if chtree(G, P, U ) = τ A (respectively τ B ), then for some U , chtree(G, P, U ) = τ .”
Quote in the paperSubstantial claim - Also stated in: § Induction Step: · plain
- Interpretationreasoning
A global tree γ is finite if it is well-quasi-ordered.
“A global tree γ is finite if it is well-quasi-ordered.”
Quote in the paperSubstantial claim - Interpretationreasoning
The definition of ca safely approximates the optimal but impractical 'more general' definition based on the set of concretizations.
“The following proposition shows that the above definition safely approximates the optimal but impractical”
Quote in the paperSubstantial claim - Interpretationreasoning
If CA ca CB and CB is a P-characteristic atom, then CA is a P-characteristic atom.
“Let P be a program and CA, CB be two characteristic atoms such that CA ca CB.If CB is a P -characteristic atom then so is CA.”
Quote in the paperSubstantial claim - Interpretationown data
By partial deduction, execution times were more than halved for the fully unfoldable benchmarks.
“i.e., by partial deduction we were able to (more than) halve execution times.”
Quote in the paperSubstantial claim - Interpretationown data
The difference between ECCE-d and ECCE-x in resulting speedups shows that determinate unfolding, at least in the context of standard partial deduction, is in general not sufficient for fully satisfactory specialization.
“The difference between ECCE-d and ECCE-x in the resulting speedups shows that determinate unfolding, at least in the context of standard partial deduction, is in general not sufficient for fully satisfactory specialization”
Quote in the paperSubstantial claim - Interpretationcitation
If R is the resultant of a finite (possibly incomplete) SLDNF-derivation of P ∪ {← A} whose characteristic path is δ, and ← Aθ resolves with R giving the resultant R_A, then there exists a finite (possibly incomplete) SLDNF-derivation of P ∪ {← Aθ} whose characteristic path is δ and whose resultant is R_A.
“If ← Aθ resolves with R giving the resultant R A then there exists a finite (possibly incomplete) SLDNFderivation of P ∪ {← Aθ} whose characteristic path is δ and whose resultant is R A .”
Quote in the paperSubstantial claim - Interpretationown data
Getting rid of higher-order overhead seems highly beneficial, yielding about one order of magnitude speedup.
“Getting rid of higherorder overhead also seems highly beneficial, yielding about one order of magnitude speedup.”
Quote in the paperNot a substantial claim - Interpretationnone given
Both unfolding rules ensure that neither the number nor the order of the solutions under Prolog execution are altered.
“Both of these unfolding rules actually ensure that neither the number nor the order of the solutions under Prolog execution are altered.”
Quote in the paperNot a substantial claim - Interpretationnone given
The method achieves this without using constraints in the partial deduction process.
“All this is achieved without using constraints in the partial deduction process.”
Quote in the paperSubstantial claim - Interpretationcitation
For a partial deduction P of P with respect to à and ρ_α such that à is a finite set of unconstrained P-characteristic atoms, à is P-covered, and G is P-covered by Ã, P ∪ {ρ_α(G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.
“(1 ) P ∪ {ρ α (G)} has an SLDNF-refutation with computed answer θ if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Interpretationreasoning
When generalizing calls to built-ins that generate bindings and are no longer executable after generalization, these built-ins have to be removed from the generalized characteristic tree.
“One problematic aspect is that, when generalizing calls to built-ins which generate bindings (like is/2 or =../2 but unlike >/2 or </2) and which are no longer executable after generalization, these built-ins have to be removed from the generalized characteristic tree (i.e., they are no longer selected).”
Quote in the paperSubstantial claim - Interpretationcitation
For a partial deduction P of P with respect to à and ρ_α such that à is a finite set of unconstrained P-characteristic atoms, à is P-covered, and G is P-covered by Ã, P ∪ {ρ_α(G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.
“(2 ) P ∪ {ρ α (G)} has a finitely failed SLDNF-tree if and only if P ∪ {G} does.”
Quote in the paperSubstantial claim - Interpretationcitation
Termination under Prolog will be preserved by these unfolding rules.
“Also, termination under Prolog will be preserved by these unfolding rules (termination behavior might however be improved, as for example ← loop, fail can be transformed into ← fail ).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Proietti and Pettorossi 1991a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Bossi and Cocco 1994 source
- cites Bossi et al. 1995
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
If A and B are atoms and τ_A is a characteristic tree of A in program P, and B is an instance of A, then there exists a characteristic tree τ_B of B in P such that τ_B ⊆ τ_A.
“If B is an instance of A then there exists a characteristic tree τ B of B in P such that τ B ⊆ τ A .”
Quote in the paperSubstantial claim - Premisecitation
≺ is a well-founded order on expressions.
“We know that ≺ is a well-founded order on expressions (see e.g., Lemma C.2 in Appendix C).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lemma C.2
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Because the inverse of the mapping . is not total, one cannot simply apply the msg on the term representation of characteristic trees in order to obtain a generalization.
“But note that, because the inverse is not total, we cannot simply apply the msg on the term representation of characteristic trees in order to obtain a generalization.”
Quote in the paperSubstantial claim - Interpretationreasoning
Under the conditions of Lemma B.2.6, if D is a finite SLDNF-derivation of P ∪ {G'} leading to the resolvent RG via c.a.s. θ, then there exists a finite SLDNF-derivation of P ∪ {G} leading to a resolvent RG via c.a.s. θ such that RG is an admissible renaming of RG under α in P and RG is P-covered by Ã.
“Then there exists a finite SLDNF-derivation of P ∪ {G} leading to a resolvent RG via c.a.s.θ such that RG is an admissible renaming of RG under α in P and such that RG is P -covered by Ã.”
Quote in the paperSubstantial claim - Interpretationreasoning
Under the conditions of Lemma B.2.5, if RG is derived from G and Cγ using θ, then there exists a goal RG such that RG is derived from G and Cγ using θ and RG is an admissible renaming of RG under α in P.
“(1 ) RG is derived from G and Cγ using θ and (2 ) RG is an admissible renaming of RG under α in P .”
Quote in the paperSubstantial claim - Interpretationreasoning
The computations of P ∪ {←ρα(G)} are totally correct with respect to P ∪ {←G}.
“We can apply Theorem B.2.12 to deduce that the computations of P ∪ {←ρ α (G)} are totally correct with respect to P ∪ {←G}.”
Quote in the paperSubstantial claim - Interpretationreasoning
For a characteristic tree τ, if δ1 ∈ τ and δ2 ∈ τ and δ2 is a prefix of δ1, then δ1 = δ2.
“If δ 2 is a prefix of δ 1 then δ 1 = δ 2 .”
Quote in the paperNot a substantial claim - Interpretationreasoning
The partial deduction P(A,τ) of a safe characteristic atom (A, τ) is a subset of a partial deduction P_A of the ordinary atom A.
“The above Lemma B.2.9 (also) establishes that the partial deduction P (A,τ ) of a safe characteristic atom (A, τ ) is a subset of a partial deduction P A of the ordinary atom A.”
Quote in the paperSubstantial claim - Interpretationreasoning
Let P be a program, G a goal, Ã a set of safe characteristic atoms, and P the union of partial deductions R(A,τ) in P, one for every element (A, τ) of Ã. If D is a finite SLD+-derivation of P ∪ {G} with computed answer θ and resultant R and every selected atom A resolved with a clause in R(A,τ) is a concretization of (A, τ), then there exists a finite SLD+-derivation of P ∪ {G} with computed答案 θ?
“Then there exists a finite SLD + -derivation of P ∪ {G} with computed answer θ and resultant R.”
Quote in the paperSubstantial claim - Premisecitation
If ← A resolves with C to G then G fails finitely in P.
“We also need the following lemma from Lloyd and Shepherdson [1991], where it is Lemma 4.10.If ← A resolves with C to G then G fails finitely in P .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lloyd and Shepherdson [1991] source
- Interpretationcitation
By Lemma F.1, NotStrictInst is a WQR on expressions.
“Hence by Lemma F.1 N otStrictInst is a WQR on expressions.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lemma F.1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationnone given
To guarantee that if τ1 ¢* τ2 holds then msg(τ1, τ2) is defined, it is sufficient to ensure that ∅ ¢* τ if and only if τ = ∅ and τ ¢* ∅ if and only if τ = ∅.
“to guarantee that if τ 1 ¢ * τ 2 holds then msg(τ 1 , τ 2 ) is defined, we simply have to ensure that -∅ ¢ * τ if and only if τ = ∅ and -τ ¢ * ∅ if and only if τ = ∅.”
Quote in the paperNot a substantial claim - Interpretationcitation
The existence of such a mapping implies, by Lemma C.2, that there are no infinite chains of strictly more general characteristic trees.
“The existence of such a mapping also implies, by Lemma C.2, that there are no infinite chains of strictly more general characteristic trees.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lemma C.2
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Reaching the fixpoint guarantees that all predicates in the bodies of resultants are precise concretizations of at least one characteristic atom in Ãk, i.e., Ãk is P-covered.
“Proof.Reaching the fixpoint guarantees that all predicates in the bodies of resultants are precise concretizations of at least one characteristic atom in Ãk , i.e., Ãk is P -covered.”
Quote in the paperSubstantial claim - Interpretationcitation
By Proposition 4.4.4, ¢ is a WQO on expressions (given a finite underlying alphabet).
“By Proposition 4.4.4we also have that ¢ is a WQO on expressions (given a finite underlying alphabet).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Proposition 4.4.4
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationcitation
Termination is guaranteed by Proposition C.4, given that the number of distinct characteristic trees is finite.
“Finally, termination is guaranteed by Proposition C.4, given that the number of distinct characteristic trees is finite.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Proposition C.4
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Classified as probably not a substantial claim. 62
- May combine two claims. 45
- The quote only partly states this claim. 2
- Borderline: one of the tests for a substantial claim is unclear. 1
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThere is an interesting relation between the control techniques presented in the article and current practice in supercompilation.
“Next, there is an interesting relation between the control techniques presented in this article and current practice in supercompilation [Glück and Sørensen 1996;Sørensen and Glück 1995;Turchin 1986;Turchin 1988].”
Quote in the paperNot a substantial claim1 of 3 sources checkedMay combine two claims.
Premisenone givenVery few abstract interpretations of logic programs use infinite domains of infinite height, and to the authors' knowledge all of them have some a priori limitation of precision, at least in practice.
“Very few abstract interpretations of logic programs use infinite domains of infinite height (some notable exceptions are Bruynooghe [1991], Janssens and Bruynooghe [1992], and Heintze [1992]), and to our knowledge all of them have some a priori limitation of the precision, at least in practice.”
Quote in the paperSubstantial claim1 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationNeighborhoods of order n, forming the basis for generalization in full supercompilation [Turchin 1988], are essentially the same as classes of atoms or goals with an identical depth-n characteristic tree.
“It is also interesting to return to an observation already made in Section 4 of Martens and Gallagher [1995]: neighborhoods of order”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Martens and Gallagher [1995] source
Section 4 (page unavailable) says that supercompilation neighborhoods reflect a computation history of order n and that this “seems to be related” to characteristic trees with depth bound n. It does not establish that neighborhoods are essentially the same as classes of atoms or goals with identical depth-n characteristic trees; the claim states the relationship more strongly than the source does. (LLM, conf=0.86)
Experimental — accuracy not yet measured - cites Turchin 1988
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA similar use of the minimization algorithm is made by Winsborough [1992] and Puebla and Hermenegildo [1995].
“A similar use of this minimization algorithm is made by Winsborough [1992] and Puebla and Hermenegildo [1995].”
Quote in the paperNot a substantial claim1 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPartial evaluation of functional-logic programs already features the use of homeomorphic embedding and m-trees.
“Indeed, partial evaluation of functional-logic programs [Alpuente et al. 1996;1997;Lafave and Gallagher 1997] already features the use of homeomorphic embedding and m-trees [Martens and Gallagher 1995].”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites Alpuente et al. 1996 source
- cites Lafave and Gallagher 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Martens and Gallagher 1995 source
Section 3 presents an m-tree-based algorithm for partial deduction, supporting the m-tree part of the attribution. The passages on termination and the algorithm do not describe using homeomorphic embedding; searches for that term and its use in termination found no supporting passage. The paper addresses logic-program partial deduction, while the functional-logic-program context is attached to the other citations in the sentence. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPuebla and Hermenegildo [1995], in a somewhat different context, studies polyvariant parallelization and specialization of logic programs based on abstract interpretation.
“The latter, in a somewhat different context, studies polyvariant parallelization and specialization of logic programs based on abstract interpretation.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Puebla and Hermenegildo [1995] source
May combine two claims.
InterpretationcitationPlugging in a depth-bound-free local control strategy yields a fully automatic, concrete partial-deduction method that always terminates and produces precise and reasonable polyvariance, without resorting to ad hoc techniques.
“Plugging in a depth-bound-free local control strategy (see Bruynooghe et al. [1992] and Martens and De Schreye [1996]), we thus obtain a fully automatic, concrete partial-deduction method that always terminates and produces precise and reasonable polyvariance, without resorting to any ad hoc techniques.”
Quote in the paperSubstantial claim1 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
FindingreasoningThe partial deduction of P with respect to à and ρα is m1(X) ← (1') and t ← m1([]), m1([b]) (2').
“Therefore the partial deduction of P with respect to à and ρ α is 7 (1') m 1 (X) ← (2') t ← m 1 ([]), m 1 ([b])”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown dataIn Example 2.4.2, the generalized atom member(a,[a|T]) has a different characteristic tree from member(a,[a,b]) and member(a,[a]), independently of the particular unfolding rule.
“Unfortunately, the generalized atom member (a, [a|T ]) has a different characteristic tree τ , independently of the particular unfolding rule.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
FindingreasoningIn Example 4.2.1, an unfolding rule based on well-founded measures could have continued unfolding more deeply for the first atom, thus avoiding the fake growing problem in this case.
“Indeed, in Example 4.2.1, an unfolding rule based on well-founded measures could have continued unfolding more deeply for the first atom, thus avoiding the fake growing problem in this case.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn practice, the complexity of the transformation does not seem to be all that bad, especially since the experiments were conducted with a prototype not yet tuned for transformation speed.
“But as the experiments in Section 5 show, in practice, the complexity of the transformation does not seem to be all that bad, especially since the experiments were still conducted with a prototype which was not yet tuned for transformation speed.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Section 5
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationCharacteristic trees might be a vital asset when trying to solve the parsing problem that appears when unfolding metainterpreters with nontrivial object programs.
“In recent experiments, it also turned out that characteristic trees might be a vital asset when trying to solve the parsing problem [Martens 1994], which appears when unfolding metainterpreters with nontrivial object programs.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Martens 1994
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Findingown dataIn Example 4.1.1, imposing a depth bound of 100 yields termination, but 100 different characteristic trees and instantiations of the accumulator arise, and the algorithm produces 100 different versions of rev, one for each characteristic tree.
“Imposing a depth bound of say 100, we obtain termination; however, 100 different characteristic trees (and instantiations of the accumulator) arise, and the algorithm produces 100 different versions of rev : one for each characteristic tree.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn Example 4.1.2, an infinite sequence of ever-growing characteristic trees results, giving nontermination without a depth bound and very unsatisfactory ad hoc specializations with it.
“An infinite sequence of ever-growing characteristic trees results, and again, as in Example 4.1.1,we obtain nontermination without a depth bound, and very unsatisfactory ad hoc specializations with it.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningIn Example 4.2.1, the atoms in the leaves of the second tree are more general than those already met, and simply continuing partial deduction without generalization will lead to natural termination without any depth bound intervention.
“However, the atoms in the leaves of the second tree are more general than those already met, and simply continuing partial deduction without generalization will lead to natural termination without any depth bound intervention.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenThe authors' methods were successfully adapted to automatically control the recently developed conjunctive partial deduction.
“We can, however, already point out that our methods were successfully adapted to automatically control the recently developed conjunctive partial deduction (see Section 6).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn the setting of unfolding metainterpreters with nontrivial object programs, a growing of the syntactic structure does not imply a growing of the characteristic tree.
“In such a setting a growing of the syntactic structure also does not imply a growing of the characteristic tree.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataECCE-x outperforms the other systems for speed and code size, and has the best worst-case performance.
“the system ECCE-x clearly outperforms the others, for speed as well as for code size, while having the best worst-case performance.”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataRemoving the depth bound drastically decreases total transformation time by a factor of 42.
“a factor of 42.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationThe benchmark programs include a set of more involved and realistic examples, such as a model-elimination theorem prover and a metainterpreter for an imperative language.
“In addition to the benchmarks by Lam and Kusalik [1990] they contain a whole set of more involved and realistic examples, for example, such as a model-elimination theorem prover and a metainterpreter for an imperative language.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lam and Kusalik 1990
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
FindingcitationFor SP, the nontermination symbol means real nontermination; for MIXTUS, heap overflow after 20 minutes; for PADDY, a thorough system crash after 2 minutes.
“-⊥, SP: this means”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Gallagher 1991 source
May combine two claims.
Findingown dataExtensive experiments with an implementation of the method showed its practical value: it outperformed existing partial-deduction systems for speedup and code size while guaranteeing termination.
“Extensive experiments with an implementation of the method showed its practical value: outperforming existing partial-deduction systems for speedup as well as code size while guaranteeing termination.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataRemoving the depth bound (ECCE-x) increases total speedup from 2.13 to 2.51 and weighted speedup from 2.23 to 2.75, while decreasing specialized code size from 235KB to 142KB.
“by removing the depth bound (ECCE-x) we increase the total speedup from 2.13 to 2.51 (and the weighted speedup from 2.23 to 2.75) while decreasing the size of the specialized code from 235KB down to 142KB.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationECCE is publicly available.
“The system which integrates the ideas of this article, called ECCE, is publicly available [Leuschel 1996]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Leuschel 1996
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenECCE is an implementation of a generic version of Algorithm 4.6.1 that allows the advanced user to change or implement the unfolding rule, the abstraction operator, and the nontermination detection method.
“The system which integrates the ideas of this article, called ECCE, is publicly available [Leuschel 1996] and is actually an implementation of a generic version of Algorithm 4.6.1, which allows the advanced user to change and even implement for example the unfolding rule as well as the abstraction operator and nontermination detection method.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFor some benchmarks the depth bound of 10 was too shallow, while for others it was too deep and caused excessive transformation times.
“for some benchmarks the depth bound of 10 was too shallow (e.g., relative) while for others it was too deep and resulted in excessive transformation times (e.g., model-elim.app).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenBy adapting the settings of ECCE, one can simulate a global tree-oriented version of Algorithm 3.4.3 using depth bounds to ensure termination.
“But one can also simulate a (global tree-oriented) version of Algorithm 3.4.3using depth bounds to ensure termination.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone givenFor some new benchmark tasks it is impossible to get big speedups; the goal of these tasks is to test whether no pessimization, code explosion, or nontermination occurs.
“For some of these new benchmark tasks it is impossible to get (big) speedups-the goal of these tasks consists in testing whether no pessimization, code explosion or nontermination occurs.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataECCE's transformation times are reasonable and usually close to those of MIXTUS.
“the transformation times are reasonable and usually close to the ones of MIXTUS.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe weighted speedup of ECCE-x is 2.75, and the speedup for the fully unfoldable benchmarks is 2.02.
“The weighted speedup of ECCE-x is 2.75, and the speedup for the fully unfoldable benchmarks is 2.02”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenBy adapting the settings of ECCE, one can obtain exactly Algorithm 4.6.1.
“For instance, by adapting the settings of ECCE, one can obtain exactly Algorithm 4.6.1.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingnone givenECCE-x-10's transformation times, weighted speedup, and size of specialized code are not so good.
“Its transformation times, weighted speedup, and size of the specialized code are not so good.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingreasoningAlgorithm 4.3.6 produces as output a characteristic tree τ such that if chtree(G, P, U) = τ_A (respectively τ_B), then for some U, chtree(G, P, U) = τ; the same holds for any τ_i arising during the execution.
“Lemma 4.3.8.Algorithm 4.3.6 terminates and produces as output a characteristic tree τ such that if chtree(G, P, U ) = τ A (respectively τ B ), then for some U , chtree(G, P, U ) = τ .The same holds for any τ i arising during the execution of Algorithm 4.3.6.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningFor all i in {1, ..., n}, vi ≤ wi, and either the abstraction operator performs no modification (and v = w) or the well-founded measure hvecT strictly decreases.
“We have that ∀i ∈ {1, . . ., n} : v i ≤ w i and either the abstraction operator performs no modification (and v = w) or the well-founded measure hvec T strictly decreases.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone givenThe inverse of the mapping ., introduced in the proof of Proposition 4.4.9, is not total but still strictly monotonic.
“Also note that the inverse of the mapping ., introduced in the proof of Proposition 4.4.9, is not total but still strictly monotonic.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Proposition 4.4.9
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenThe global tree in Figure 6 also contains two nodes which are variants of their parent node.
“The global tree in Figure6also contains two nodes which are variants of their parent node.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Figure 6
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
FindingreasoningIn the member program from Example 2.3.4, with A = member(a, [a]), τ = {1:1, 1:2} and τ' = {1:1}, γP(A, τ) = γP(A, τ') = {member(a, [a])}, but neither (A, τ) ca (A, τ') nor (A, τ') ca (A, τ) hold.
“Take the member program from Example 2.3.4,and let A = member (a, [a]), τ = { 1 : 1 , 1 : 2 } and τ = { 1 : 1 }.Then γ P (A, τ ) = γ P (A, τ ) = {member(a, [a])} (because the resolvent ← member (a, []) associated with 1 : 2 fails finitely), but neither (A, τ ) ca (A, τ ) nor (A, τ ) ca (A, τ ) hold.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Example 2.3.4
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Interpretationnone givenAlthough the abstraction operator chabs_P,U performs well in many practical cases, it does not always preserve characteristic trees, causing sometimes severe loss of precision and specialization.
“Unfortunately, although for a lot of practical cases chabs P,U performs quite well, it does not always preserve the characteristic trees, entailing a sometimes quite severe loss of precision and specialization.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Interpretationnone givenThe characteristic tree captures all the relevant aspects of specialization attained by local control for a particular atom.
“The characteristic tree captures all the relevant aspects of specialization, attained by the local control for a particular atom:”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Interpretationnone givenThe set of concretizations associated with a characteristic atom is downward closed (closed under substitution).
“Note that by definition the set of concretizations associated with a characteristic atom is downward closed (or closed under substitution).”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningAn abstraction operator that uses the most specific generalization based on syntactic structure is unsatisfactory because it involves an ad hoc maximum number and because syntactic structure does not reflect context-dependent specialization behavior.
“This approach is however unsatisfactory.First, it involves an ad hoc maximum number, which might lead to either too much or too little polyvariance, depending on the context.Second, the msg is just based on the syntactic structure of the atoms to be specialized.This is generally not such a good idea.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningA specialization aspect not captured by a characteristic tree is how the atoms in the leaves of the associated SLDNF-tree are further specialized; global control and precision are not captured.
“A specialization aspect that does not materialize within a characteristic tree is how the atoms in the leaves of the associated SLDNF-tree are further specialized, i.e., the global control and precision are not captured.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe paper solves the two problems of preserving characteristic trees upon generalization and eliminating the ad hoc depth bound.
“In the present article, we solve these two problems.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe syntactic structures of atoms alone provide insufficient information for satisfactory control of polyvariance, and a refined abstraction operator should also take the associated SLDNF-trees into consideration.
“This illustrates that the syntactic structures of B and C alone provide insufficient information for a satisfactory control of polyvariance and that a refined abstraction operator should also take the associated SLDNF-trees into consideration.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningBy examining only nonfailing branches, the characteristic tree does not capture how exactly some branches were pruned, but this is adequate and beneficial.
“By examining only the nonfailing branches we do not capture how exactly some branches were pruned.The following example illustrates why this is adequate and even beneficial.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
InterpretationreasoningThe concretizations of an unconstrained characteristic atom are identical to the instances of its ordinary atom component.
“The concretizations of an unconstrained characteristic atom (A, τ A ) are identical to the instances of the ordinary atom A (because the concretizations are downward closed, and γ P (A, τ ) contains no atom strictly more general than A).”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningFailure to preserve characteristic trees upon generalization may lead to significant losses in specialization and to problems for termination of the partial deduction process.
“This may lead to significant losses in specialization, as well as to problems for the termination of the partial deduction process.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe practical relevance and benefits of the proposed approach are illustrated through extensive experiments.
“The practical relevance and benefits of the work are illustrated through extensive experiments.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Interpretationnone givenA is a precise concretization of chatom(A, P, U).
“Note that A is a precise concretization of chatom(A, P, U )”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningFailing branches do not materialize within the resultants, and a single resultant can be used for atoms with the same characteristic tree without losing specialization.
“However, this is of no relevance, because the failing branches do not materialize within the resultants (i.e., the specialized code generated for the atoms), and furthermore the single resultant member (a, [a|T ]) ← could be used for both A and B without loosing any specialization.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationnone givenAlgorithm 4.3.6 produces as output a characteristic tree τ such that if chtree(G, P, U) = τA or τB, then for some U, chtree(G, P, U) = τ.
“Algorithm 4.3.6 terminates and produces as output a characteristic tree τ such that if chtree(G, P, U ) = τ A (respectively τ B ), then for some U , chtree(G, P, U ) = τ .”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe partial deduction method of Gallagher [1991] was extended by de Waal [1994] by adorning characteristic trees with a depth-k abstraction of the corresponding atom component.
“the partial deduction method of Gallagher [1991] was extended by de Waal [1994] by adorning characteristic trees with a depth-k abstraction of the corresponding atom component.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Gallagher [1991] source
- cites de Waal [1994]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningNormalizing characteristic trees by imposing a fixed (e.g., left-to-right) computation rule and delaying the selection of all negative literals to the end solves the problem of characteristic trees carrying too much information.
“A quite simple solution to this problem exists: after having performed the local unfolding we just have to normalize the characteristic trees by imposing a fixed (e.g., left-to-right) computation rule and delaying the selection of all negative literals to the end.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationAlgorithm 4.6.1 can be seen as performing an abstract interpretation on an infinite domain of infinite height (the ascending chain condition of Cousot and Cousot [1992] is not satisfied) and without a priori limitation of precision.
“Algorithm 4.6.1 can also be seen as performing an abstract interpretation on an infinite domain of infinite height (i.e., the ascending chain condition of Cousot and Cousot [1992] is not satisfied) and without a priori limitation of the precision (i.e., if possible, we do not perform any abstraction at all and obtain simply the concrete results).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Cousot and Cousot [1992] source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenThese nodes in the marked partial process tree only contain syntactical information corresponding to ordinary atoms (or rather goals).
“These nodes, however, only contain syntactical information corresponding to ordinary atoms (or rather goals; see Section 6).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIn Sørensen and Glück [1995], a generalization strategy for positive supercompilation (no negative information propagation while driving) is proposed.
“In the latter, a generalization strategy for positive supercompilation (no negative information propagation while driving) is proposed.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sørensen and Glück [1995] source
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Study design and conductnone givenThe results and discussions of the article remain valid independently of whether the normalization of characteristic trees is applied or not.
“The results and discussions of this article remain valid, independently of whether this normalization is applied or not.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenThe authors' method is free of ad hoc depth bounds and, without the Section 4.8 postprocessing, nevertheless obtains a similar effect to de Waal's depth-k abstraction.
“Our method is free of any such bounds and (without the Section 4.8 postprocessing) nevertheless obtains a similar effect.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataComputations influenced by one or more growing data structures are not so rare after all, and they cause ad hoc behavior of partial deduction where global control is founded on characteristic trees with a depth bound.
“Summarizing, computations influenced by one or more growing data structures are not so rare after all, and they cause ad hoc behavior of partial deduction, where the global control is founded on characteristic trees with a depth bound.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe global control method as laid out in Section 4 has considerable complexity as a possible drawback.
“Returning to the global control method as laid out in Section 4, one can observe that a possible drawback might be its considerable complexity.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe msg for characteristic atoms is a most specific generalization and is unique up to variable renaming.
“Note that the above msg for characteristic atoms is indeed a most specific generalization (because msg(A 1 , A 2 ) and msg(τ 1 , τ 2 ) are most specific generalizations for the atom and characteristic tree parts respectively) and is still unique up to variable renaming.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenSuch duplicated polyvariance is superfluous (in the context of simply running the resulting program) when it increases neither local nor global precision.
“Such”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe generalization strategy in Sørensen and Glück [1995] uses ¢ to compare nodes in a marked partial process tree, a notion originating from Glück and Klimov [1993] and corresponding to global trees in partial deduction.
“It uses ¢ to compare nodes in a marked partial process tree: a notion originating from Glück and Klimov • 241 [1993] and corresponding to global trees in partial deduction.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Glück and Klimov [1993] source
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenTesting for well-quasi-ordering unavoidably entails searching and repeated comparisons with several ancestors.
“Testing for well-quasi-ordering, however, unavoidably does entail such searching and repeated comparisons with several ancestors.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Interpretationown dataThe homeomorphic embedding relation ¢ as defined in Definition 4.4.2 is rather crude with respect to variables; all variables are treated as if they were the same variable.
“However, as can be observed in Example 4.4.3, the homeomorphic embedding relation ¢ as defined in Definition 4.4.2 is rather crude with respect to variables.In fact, all variables are treated as if they were the same variable, a practice which is undesirable in a logic programming context.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA similar effect to normalization can be obtained, in the context of definite programs, via the trace terms of Gallagher and Lafave [1996].
“A similar effect can be obtained, in the context of definite programs, via the trace terms of Gallagher and Lafave [1996].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Gallagher and Lafave [1996] source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe depth-k abstraction in de Waal's extension was done to increase polyvariance so that a monovariant postprocessing abstract interpretation phase detecting useless clauses can obtain a more precise result.
“This was done in order to increase the amount of polyvariance so that a (monovariant) postprocessing abstract interpretation phase (detecting useless clauses) can obtain a more precise result.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites de Waal [1994]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Interpretationreasoningp(X, X) can be seen as standing for something like and(eq(X, Y), p(X, Y)), which clearly embeds p(X, Y), but the reverse does not hold.
“Indeed p(X, X) can be seen as standing for something like and(eq(X, Y ), p(X, Y )), which clearly embeds p(X, Y ), but the reverse does not hold.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe conditions of Definition 4.4.8 are essential for the termination of Algorithm 4.6.1.
“The conditions of Definition 4.4.8 are essential for the termination of a Algorithm 4.6.1.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe complexity of the minimization algorithm is O(kn^2), where n is the maximum number of states and k is the number of symbols.
“As stated by Hopcroft and Ullman [1979], the complexity of this algorithm is O(kn 2 ), where n is the maximum number of states (in our case the number of characteristic atoms), and k is the number of symbols (in our case the maximum number of leaf atoms).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hopcroft and Ullman [1979]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe generalization strategy as well as the generation of polyvariance in functional-logic partial evaluation remains entirely based on syntactic structure of the manipulated expressions.
“On the other hand, the generalization strategy as well as the generation of polyvariance remains entirely based on syntactic structure of the manipulated expressions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenTo the best of the authors' knowledge, this is the very first such method.
“To the best of our knowledge, this is the very first such method.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe homeomorphic embedding relation of Definition 4.4.2 has to be adapted because some built-ins can dynamically construct infinitely many new constants and functors, so it is no longer a well-quasi-order.
“Also, the homeomorphic embedding relation ¢ of Definition 4.4.2(and the relations ¢ * and ¢ * ca based on it) has to be adapted.Indeed, some built-ins (like = ../2 or is/2) can be used to dynamically construct infinitely many new constants and functors, and thus ¢ is no longer a WQO.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWinsborough [1992] aims at minimizing polyvariance in the context of multiple specialization by optimizing compilers.
“The former aims at minimizing polyvariance in the context of multiple specialization by optimizing compilers.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Winsborough [1992] source
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenMIXTUS-like unfolding seems to be a good compromise for standard partial deduction.
“The”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenThe quality of the specialization produced by any fully concrete instance of Algorithm 4.6.1 depends heavily on the quality of the specific local control used.
“the quality of the specialization produced by any fully concrete instance of Algorithm 4.6.1 will obviously also depend heavily on the quality of the specific local control used.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningWith the removal of non-executable built-ins from generalized characteristic trees, the concretization definition for characteristic atoms scales up, and the technique ensures correct specialization.
“With that, the concretization definition for characteristic atoms scales up, and the technique will ensure correct specialization.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The Prolog built-ins handled by ECCE are declarative.
May combine two claims.
Interpretationnone givenThe abstraction operator preserves the characteristic trees of the atoms to be specialized and ensures termination when the number of distinct characteristic trees is bounded, while providing fine-grained control of polyvariance.
“the abstraction operator of the algorithm preserves the characteristic trees of the atoms to be specialized and ensures termination (when the number of distinct characteristic trees is bounded) while providing a fine-grained control of polyvariance.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationcitationThe global control techniques presented in the article can be extended and significantly contribute in the context of more powerful unfold/fold-like transformations.
“It turned out that the global control techniques presented in the current article can be extended and that they significantly contribute in that context too”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Leuschel et al. [1996]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Glück et al. [1996]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Leuschel [1997a]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based). May combine two claims.
PremisecitationMIXTUS-like unfolding is the unfolding strategy explained by Sahlin [1991;1993], which in general unfolds deeply enough to solve the fully unfoldable problems, but also has safeguards against excessive unfolding and code explosion.
“-”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Sahlin 1991
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Sahlin 1993 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown dataSP seems to employ a refined determinate unfolding rule, as indicated by the results for the benchmark depth.lambelow.
“Note however that SP seems to employ a refined determinate unfolding rule (as indicated for example by the results for the benchmark depth.lambelow).”
Quote in the paperNot a substantial claimBorderline on S4 (based): unclear from the text.
Interpretationnone givenThe resulting specializer improves significantly upon earlier work with respect to speed and size of the specialized programs.
“The resulting specializer improves significantly upon earlier work with respect to speed and size of the specialized programs.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe MIXTUS-like unfolding strategies of ECCE, MIXTUS, and PADDY differ slightly from each other, probably due to details not fully elaborated in Sahlin [1993] and Prestwich [1992a] and the different global control regimes.
“Note that the”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Sahlin 1993 source
- cites Prestwich 1992a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Study design and conductnone givenSufficient memory was given to the Prolog system to prevent garbage collection.
“Sufficient memory was given to the Prolog system to prevent garbage collection.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMIXTUS-like unfolding requires a number of ad hoc settings.
“It requires, however, a number of ad hoc settings.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sahlin 1993 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe benchmark programs were carefully selected and/or designed to cover a wide range of different application areas.
“The benchmark programs were carefully selected and/or designed in such a way that they cover a wide range of different application areas”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAs proven by Leuschel [1997b], it is possible to perform the not-strict-instance test for the embedding relation recursively within the structure of the expressions.
“Furthermore, as proven by Leuschel [1997b], it is possible to perform the”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Leuschel 1997b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenTransformation times of ECCE and MIXTUS include the time to write the specialized program to file; time for SP does not; for PADDY it is unknown.
“-Transformation times (TT): The transformation times of ECCE and MIXTUS include the time to write the specialized program to file.Time for SP does not, and for PADDY we do not know.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
Interpretationown dataThe ideas presented in the article make sense in theory on accounts of elegance, generality, precision, and termination, and they also pay off in practice.
“the ideas presented in this article do not only make sense in theory on accounts of elegance, generality, precision, and termination, but they also pay off in practice.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataAll timings were for renamed queries, except for the original programs and for SP; SP does not rename the top-level query, putting SP at a disadvantage of about 10% in average for speed but at an advantage for code size.
“All timings were for renamed queries, except for the original programs and for SP (which does not rename the top-level query-this puts SP at a disadvantage of about 10% in average for speed, but at an advantage for code size).”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenThe framework and the algorithm can handle normal logic programs and place no restrictions on the unfolding rule.
“The framework and the algorithm can handle normal logic programs and place no restrictions on the unfolding rule.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningThe possibility of calling the specialized program in an unrenamed style was not used in the benchmarks, but avoids distortions in the code size figures.
“This possibility was not used in the benchmarks, but avoids distortions in the code size figures (with respect to MIXTUS and ECCE).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenIn computing averages and totals, the time and size of the original program were taken in case of nontermination, so MIXTUS, PADDY, and SP were not punished for nontermination.
“In computing averages and totals, the time and size of the original program were taken in case of nontermination (i.e., we did not punish MIXTUS, PADDY, and SP for the nontermination).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenDeterminate unfolding selects only, except once, atoms that match a single clause head, and is refined with a lookahead to detect failure at a deeper level.
“-Determinate unfolding: Only (except once) select atoms that match a single clause head.The strategy is refined with a”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningBecause any instance of an atom in the goal G is a precise concretization of a characteristic atom in Ã0, the conditions of Theorem 3.3.2 are satisfied for goals G whose atoms are instances of atoms in G, i.e., G is P-covered by Ãk.
“Hence, because any instance of an atom in the goal G is a precise concretization of a characteristic atom in Ã0 , the conditions of Theorem 3.3.2are satisfied for goals G whose atoms are instances of atoms in G, i.e., G is P -covered by Ãk .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Theorem 3.3.2
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenAll results so far also hold for multisets of characteristic atoms.
“However, this poses no problems, as all results so far also hold for multisets of characteristic atoms.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenUsually, atoms which are variants of one of their ancestor nodes will not be added to the global tree, as they do not give rise to further specialization.
“Usually, atoms which are variants of one of their ancestor nodes will not be added to the global tree, as they do not give rise to further specialization.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMarlet [1994] also proposes to consider all possible numberings, but leading to n! complexity, where n is the number of variables in the terms to be compared.
“Marlet [1994] also proposes to consider all possible numberings, but (leading to n! complexity, where n is the number of variables in the terms to be compared).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Marlet [1994]
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe definition of . does not make the notion of an msg for characteristic trees, as well as Algorithm 4.3.6, superfluous.
“In other words, the definition of .does not make the notion of an msg for characteristic trees, as well as Algorithm 4.3.6,superfluous.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Algorithm 4.3.6
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe FAR filtering algorithm of Leuschel and Sørensen [1996] can be used to further improve the specialized program by removing the redundant argument of m1.
“The FAR filtering algorithm ofLeuschel and Sørensen [1996] can be used to further improve the specialized program by removing the redundant argument of m 1 .”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Leuschel and Sørensen [1996]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
The authors state this as an assumption.
The alphabet A_P underlying the programs and queries contains only finitely many constant, function, and predicate symbols.
“Remember that it may contain symbols occurring in no program and query but that it contains only finitely many constant, function, and predicate symbols.”
The authors state this as an assumption.
The Prolog built-ins handled by ECCE are declarative.
“All built-ins are supposed to be declarative and their selection delayed until they are sufficiently instantiated.”
The authors state this as an assumption.
Without loss of generality, the top-level query can be assumed to be the unrenamed atom new(X1, ..., Xk), where new is a fresh predicate symbol and vars(G) = {X1, ..., Xk}.
“without loss of generality, we can assume that the top-level query is the unrenamed atom new(X 1 , . . ., X k ), where new is a fresh predicate symbol and where vars(G) = {X 1 , . . ., X k }.”
The paper relies on this without support.
For some benchmark tasks it is impossible to get significant speedups.
“for some benchmark tasks it is impossible to get significant speedups.”
The authors state this as an assumption.
The axiom of choice holds.
“The proof will make use of the axiom of choice at several places.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Ecce can only handle declarative programs and therefore could not be applied on the ng unify benchmark.
“Note that ecce can only handle declarative programs, and could therefore not be applied on the ng unify benchmark.”
From Efficient Specialisation in Prolog Using the Hand-Written Compiler Generator LOGEN (2000) · cites this paper as [8]
Section 5.1 (Systems; page not provided) says ECCE assumes its supported Prolog built-ins are declarative, which supports a narrower version of the claimed restriction. Our copy does not say ECCE can handle only declarative programs or identify an “ng unify” benchmark that it could not handle. Its reported experiments instead include ground-unification benchmarks (Section 5.3). (LLM, conf=0.78)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Narrative code sizes disagree with Table II
MinorThe narrative says code size falls from 235 KB to 142 KB, whereas Table II reports 224.35 KB for ECCE-x-10 and 135.91 KB for ECCE-x. Neither difference is ordinary rounding to whole kilobytes.
“while decreasing the size of the specialized code from 235KB down to 142KB.”
“ECCE-x-10 224.35 112.72 ECCE-x 135.91 2.70”
Fully unfoldable speedup is reported as the non-fully-unfoldable value
MinorThe text gives 2.02 as ECCE-x's speedup for fully unfoldable benchmarks, but Table I lists 8.36 under "FU" and 2.02 under "Not FU."
“The weighted speedup of ECCE-x is 2.75, and the speedup for the fully unfoldable benchmarks is 2.02”
“ECCE-x 2.51 2.75 0.92 8.36 2.02”
Cites
Lecture Notes in Computer Science 1205
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Self-citation
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Research works printed but not linked: 10
- 10.5555/645391.651434 · DOI
- 10.5555/645392.651460 · DOI
- 10.5555/647372.724055 · DOI
- 10.5555/647372.724051 · DOI
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- 10.5555/647372.724047 · DOI
- 10.5555/12069.12121 · DOI
- 10.5555/203429.203434 · DOI
- 10.5555/647372.724048 · DOI
- TURCHIN , V. F. 1988. The algorithm of generalization in the supercompiler . In Partial Evaluation and Mixed Computation, D. BjCrner , A. P. Ershov, and N. D. Jones, Eds. North-Holland , 531- 549.]] TURCHIN, V. F. 1988. The algorithm of generalization in the supercompiler. In Partial Evaluation and Mixed Computation, D. BjCrner, A. P. Ershov, and N. D. Jones, Eds. North-Holland, 531- 549.]]
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Conjunctive partial deduction: foundations, control, algorithms, and experiments
De Schreye, D., Glück, R., Jørgensen, J., Leuschel, M., Martens, B., & Sørensen, M. H. (1999) · The Journal of Logic Programming · doi:10.1016/s0743-1066(99)00030-8 · Cited by 96 · see citing works
Self-citationPartial evaluation of functional logic programs
Alpuente, M., Falaschi, M., & Vidal, G. (1998) · ACM Transactions on Programming Languages and Systems · doi:10.1145/291891.291896 · Cited by 89 · see citing works
On the Power of Homeomorphic Embedding for Online Termination
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Self-citationLogic program specialisation through partial deduction: Control issues
Leuschel, M., & Bruynooghe, M. (2002) · Theory and Practice of Logic Programming · doi:10.1017/s147106840200145x · Cited by 74 · see citing works
Self-citationInfinite State Model Checking by Abstract Interpretation and Program Specialisation
Leuschel, M., & Massart, T. (2000) · Lecture notes in computer science · doi:10.1007/10720327_5 · Cited by 77 · see citing works
Self-citationThe narrowing-driven approach to functional logic program specialization
Albert, E., & Vidal, G. (2002) · New Generation Computing · doi:10.1007/bf03037257 · Cited by 54 · see citing works
Homeomorphic Embedding for Online Termination of Symbolic Methods
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Self-citationGeneralization strategies for the verification of infinite state systems
Fioravanti, F., Pettorossi, A., Proietti, M., et al. (2012) · Theory and Practice of Logic Programming · doi:10.1017/s1471068411000627 · Cited by 44 · see citing works
Offline specialisation in Prolog using a hand-written compiler generator
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Self-citationProgram verification via iterated specialization
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Advanced Techniques for Logic Program Specialisation
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Self-citationSecher, J. P., & Sørensen, M. H. (2000) · Lecture notes in computer science · doi:10.1007/3-540-46562-6_10 · Cited by 30 · see citing works
Coverability of Reset Petri Nets and Other Well-Structured Transition Systems by Partial Deduction
Leuschel, M., & Lehmann, H. (2000) · Lecture notes in computer science · doi:10.1007/3-540-44957-4_7 · Cited by 30 · see citing works
Self-citationCreating specialised integrity checks through partial evaluation of meta-interpreters
Leuschel, M., & De Schreye, D. (1998) · The Journal of Logic Programming · doi:10.1016/s0743-1066(97)10012-7 · Cited by 29 · see citing works
Self-citationSolving coverability problems of petri nets by partial deduction
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Alpuente, M., Falaschi, M., Moreno, G., et al. (2003) · Theoretical Computer Science · doi:10.1016/j.tcs.2003.10.033 · Cited by 27 · see citing works
Specialising Interpreters Using Offline Partial Deduction
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Self-citationProgram specialisation and abstract interpretation reconciled
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Self-citationAutomated Strategies for Specializing Constraint Logic Programs
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Model checking object petri nets in prolog
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Self-citationSelf-tuning resource aware specialisation for prolog
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The Ecce and Logen partial evaluators and their web interfaces
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Self-citationPoly-controlled partial evaluation
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Efficient Local Unfolding with Ancestor Stacks for Full Prolog
Puebla, G., Albert, E., & Hermenegildo, M. V. (2005) · Lecture notes in computer science · doi:10.1007/11506676_10 · Cited by 14 · see citing works
Forward Slicing by Conjunctive Partial Deduction and Argument Filtering
Leuschel, M., & Vidal, G. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-31987-0_6 · Cited by 13 · see citing works
Self-citationBinding-Time Annotations without Binding-Time Analysis
Vanhoof, W., & Bruynooghe, M. (2001) · Lecture notes in computer science · doi:10.1007/3-540-45653-8_49 · Cited by 12 · see citing works
Martin, J., & Leuschel, M. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-46562-6_9 · Cited by 12 · see citing works
Self-citationEfficient Specialisation in Prolog Using the Hand-Written Compiler Generator LOGEN
Leuschel, M., & Jørgensen, J. (2000) · Electronic Notes in Theoretical Computer Science · doi:10.1016/s1571-0661(05)80636-x · Cited by 11 · see citing works
Self-citationProgram Specialization for Verifying Infinite State Systems: An Experimental Evaluation
Fioravanti, F., Pettorossi, A., Proietti, M., et al. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-20551-4_11 · Cited by 11 · see citing works
Anti-unification in Constraint Logic Programming
Yernaux, G., & Vanhoof, W. (2019) · Theory and Practice of Logic Programming · doi:10.1017/s1471068419000188 · Cited by 11 · see citing works
Binding-Time Analysis by Constraint Solving
Vanhoof, W. (2007) · Springer eBooks · doi:10.1007/3-540-44404-1_25 · Cited by 11 · see citing works
Efficient and flexible access control via Jones-optimal logic program specialisation
Barker, S., Leuschel, M., & Varea, M. (2008) · LISP and Symbolic Computation · doi:10.1007/s10990-008-9030-8 · Cited by 11 · see citing works
Self-citationClosed Symbolic Execution for Verifying Program Termination
Vidal, G. (2012) · IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM) · doi:10.1109/scam.2012.13 · Cited by 10 · see citing works
Supervising Offline Partial Evaluation of Logic Programs Using Online Techniques
Leuschel, M., Craig, S.-J., & Elphick, D. (2007) · Springer eBooks · doi:10.1007/978-3-540-71410-1_5 · Cited by 10 · see citing works
Self-citationSpecialization with clause splitting for deriving deterministic constraint logic programs
Fioravanti, F., Pettorossi, A., & Proietti, M. (2005) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2002.1167971 · Cited by 10 · see citing works
Abstract Conjunctive Partial Deduction Using Regular Types and Its Application to Model Checking
Leuschel, M., & Grüner, S. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45607-4_6 · Cited by 10 · see citing works
Self-citationTowards Provably Correct Code Generation via Horn Logical Continuation Semantics
Wang, Q., Gupta, G., & Leuschel, M. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-30557-6_9 · Cited by 9 · see citing works
Self-citationTowards Just-In-Time Partial Evaluation of Prolog
Bolz, C. F., Leuschel, M., & Rigo, A. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12592-8_12 · Cited by 9 · see citing works
Self-citationSome achievements and prospects in partial deduction
Leuschel, M., Martens, B., & Schreye, D. D. (1998) · ACM Computing Surveys · doi:10.1145/289121.289125 · Cited by 9 · see citing works
Self-citationFast offline partial evaluation of logic programs
Leuschel, M., & Vidal, G. (2014) · Information and Computation · doi:10.1016/j.ic.2014.01.005 · Cited by 8 · see citing works
Self-citationSpecialization with Constrained Generalization for Software Model Checking
Angelis, E. D., Fioravanti, F., Pettorossi, A., et al. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38197-3_5 · Cited by 8 · see citing works
Termination of Floating-Point Computations
Serebrenik, A., & Schreye, D. D. (2005) · Journal of Automated Reasoning · doi:10.1007/s10817-005-6546-z · Cited by 8 · see citing works
Advanced Logic Program Specialisation
Leuschel, M. (1999) · Lecture notes in computer science · doi:10.1007/3-540-47018-2_11 · Cited by 8 · see citing works
Self-citationAlpuente, M., Cuenca-Ortega, A., Escobar, S., et al. (2020) · Fundamenta Informaticae · doi:10.3233/fi-2020-1991 · Cited by 7 · see citing works
Declarative programming for verification
Leuschel, M. (2008) · doi:10.1145/1389449.1389450 · Cited by 7 · see citing works
Self-citationFast Offline Partial Evaluation of Large Logic Programs
Leuschel, M., & Vidal, G. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-00515-2_9 · Cited by 7 · see citing works
Self-citationHomeomorphic Embedding Modulo Combinations of Associativity and Commutativity Axioms
Alpuente, M., Cuenca-Ortega, A., Escobar, S., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-13838-7_3 · Cited by 6 · see citing works
Controlling Polyvariance for Specialization-based Verification
Fioravanti, F., Pettorossi, A., Proietti, M., et al. (2013) · Fundamenta Informaticae · doi:10.3233/fi-2013-845 · Cited by 6 · see citing works
Inductive Theorem Proving by Program Specialisation: Generating Proofs for Isabelle Using Ecce
Lehmann, H., & Leuschel, M. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-25938-1_1 · Cited by 6 · see citing works
Self-citationSolving Planning Problems by Partial Deduction
Lehmann, H., & Leuschel, M. (2007) · Lecture Notes in Artificial Intelligence · doi:10.1007/3-540-44404-1_29 · Cited by 6 · see citing works
Self-citationProbabilistic Termination of CHRiSM Programs
Sneyers, J., & Schreye, D. D. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-32211-2_15 · Cited by 5 · see citing works
Automatic verification of counter systems via domain-specific multi-result supercompilation
Klimov, A. V., Klyuchnikov, I. G., & Romanenko, S. A. (2012) · Cited by 5 · see citing works
A New Termination Approach for Specialization
Song, L., & Futamura, Y. (2000) · Lecture notes in computer science · doi:10.1007/3-540-45350-4_8 · Cited by 5 · see citing works
Poly-controlled partial evaluation in practice
Ochoa, C., & Puebla, G. (2007) · doi:10.1145/1244381.1244407 · Cited by 5 · see citing works
Type-based homeomorphic embedding for online termination
Albert, E., Gallagher, J. P., Gómez‐Zamalloa, M., et al. (2009) · Information Processing Letters · doi:10.1016/j.ipl.2009.04.016 · Cited by 4 · see citing works
Removing Superfluous Versions in Polyvariant Specialization of Prolog Programs
Ochoa, C., Puebla, G., & Hermenegildo, M. V. (2006) · Lecture notes in computer science · doi:10.1007/11680093_6 · Cited by 4 · see citing works
Derivation of Efficient Logic Programs by Specialization and Reduction of Nondeterminism
Pettorossi, A., Proietti, M., & Renault, S. (2005) · LISP and Symbolic Computation · doi:10.1007/s10990-005-7008-3 · Cited by 4 · see citing works
Type-Based Homeomorphic Embedding and Its Applications to Online Partial Evaluation
Albert, E., Gallagher, J. P., Gómez‐Zamalloa, M., et al. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-78769-3_3 · Cited by 4 · see citing works
Provably Correct Code Generation: A Case Study
Wang, Q., & Gupta, G. (2005) · Electronic Notes in Theoretical Computer Science · doi:10.1016/j.entcs.2004.11.008 · Cited by 3 · see citing works
LIX: an Effective Self-applicable Partial Evaluator for Prolog
Craig, S.-J., & Leuschel, M. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24754-8_8 · Cited by 3 · see citing works
Self-citationSymbolic execution as a basis for termination analysis
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Model Checking Object Petri Nets in Maude and Prolog
Farwer, B., & Leuschel, M. (2004) · Cited by 2 · see citing works
Self-citationAutomatic JIT Compiler Generation with Runtime Partial Evaluation
Bolz, C. F., Aurich, V., & Leuschel, M. (2008) · Cited by 2 · see citing works
Self-citationA framework for bottom up specialisation of logic programs
Vanhoof, W., Schreye, D. D., & Martens, B. (1998) · Lecture notes in computer science · doi:10.1007/bfb0056607 · Cited by 2 · see citing works
Self-citationEfficient local unfolding with ancestor stacks
Puebla, G., Albert, E., & Hermenegildo, M. V. (2010) · Theory and Practice of Logic Programming · doi:10.1017/s1471068409990263 · Cited by 2 · see citing works
Abstract conjunctive partial deduction for the analysis and compilation of coroutines
Nys, V., & Schreye, D. D. (2016) · Formal Aspects of Computing · doi:10.1007/s00165-016-0389-8 · Cited by 2 · see citing works
Lehmann, H., & Leuschel, M. (2003) · ePrints Soton (University of Southampton) · Cited by 1 · see citing works
Self-citationTransformation Systems and Nondeclarative Properties
Bossi, A., Cocco, N., & Etalle, S. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45628-7_8 · Cited by 1 · see citing works
A Study on the Practicality of Poly-Controlled Partial Evaluation
Ochoa, C., & Puebla, G. (2007) · Electronic Notes in Theoretical Computer Science · doi:10.1016/j.entcs.2007.01.008 · Cited by 1 · see citing works
Generalization Strategies for the Verification of Infinite State SystemsPreprint
Fioravanti, F., Pettorossi, A., Proietti, M., et al. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1110.0999 · Cited by 1 · see citing works
Fioravanti, F., Pettorossi, A., & Proietti, M. (2002)
Partial Evaluation of Multi-Paradigm
Languages, D. (2001)
Partial Evaluation of Large Logic Programs
Oine, F., Leuschel, M., & Vidal, G. (2008)
Self-citationDerivation of Efficient Logic Programs by Specialization and Reduction of Nondeterminism
Pettorossi, A., Proietti, M., & Renault, S. (2008) · Springer eBooks · doi:10.1007/978-1-4020-6585-9_12
Partial evaluation of multidparadigm declarative languages: Thesis
Albert, E. (2001) · AI Communications
Derivation of Efficient Logic Programs by Specialization and Reduction of NondeterminismPreprint
Pettorossi, A., Proietti, M., & Renault, S. (2003) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0311044
Partial Evaluation of Rewriting Logic Theories
Ortega, A. C. (2019) · doi:10.4995/thesis/10251/130206
Analysis and Transformation of Constrained Horn Clauses for Program Verification
Angelis, E. D., Fioravanti, F., Gallagher, J. P., Hermenegildo, M. V., Pettorossi, A., & Proietti, M. (2021) · Theory and Practice of Logic Programming · doi:10.1017/s1471068421000211
Marlet, R. (2012) · doi:10.1002/9781118576984.biblio
- Authors
- Leuschel, M., Martens, B., & De Schreye, D.
- Affiliations
- Katholieke Univ. Leuven, Heverlee, Belgium
- KU Leuven (BE)
- Venue
- ACM Transactions on Programming Languages and Systems
- Published
- 1998-01
- Volume
- 20
- Issue
- 1
- Pages
- 208-258
- ISSN
- 0164-0925 (ISSN-L)
- 1558-4593
- OpenAlex
- W2137818097
- Semantic Scholar
- f303c1fe75747f1be2f55658fe426107a2ac4037
- Cited by
- 88
- References
- 91
- Citations by year
- 2021: 1 · 2020: 1 · 2019: 3 · 2016: 1 · 2015: 1 · 2014: 2 · 2013: 2 · 2012: 5
- FWCI
- 10.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Transactions on Programming Languages and Systems (publishedVersion)
- Lirias (acceptedVersion, other-oa)
- Funders
- Università degli Studi di Padova
- Vlaamse regering
- Topics
- Physical Sciences › Computer Science › Software › Logic, programming, and type systems
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Information Systems › Advanced Database Systems and Queries
- Keywords
- partial deduction, normal logic programs, program specialization, generalization, global control, termination, causal relationship, supercompilation, abstract interpretation, infinite domains
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-19.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-19.
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