On derived dependencies and connected databases

Dart, Philip W.

doi:10.1016/0743-1066(91)90017-j

Cited by 37 publications

(24 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In [5] it is proved that the information for ground-dependency analysis of Sharing is expressed by a more abstract domain, which we show to coincide with the domain Def . Def was introduced by Dart in [14] for groundness analysis in deductive databases, and used by Marriott and Søndergaard for ground-dependency analysis in [22]. As expected, the complement of Def with respect to Sharing, called Sharing + , captures precisely variable aliasing and no ground-dependency information, and shares with Sharing an elegant representation.…”

Section: Introductionmentioning

confidence: 98%

“…In particular, in [5] it has been shown that Sharing enjoys a Galois insertion with a more abstract domain that completely captures its ability to express ground-dependency. We show that indeed this domain coincides with the domain Def , introduced by Dart in [14]. It is natural then to try to characterize what is left of Sharing once we take Def out of it, i.e.…”

Section: Functional Programming: Complementing Comportment Analysismentioning

confidence: 99%

See 1 more Smart Citation

Complementation in abstract interpretation

Cortesi

Filé

Ranzato

et al. 1997

ACM Trans. Program. Lang. Syst.

View full text Add to dashboard Cite

Abstract. The reduced product of abstract domains is a rather well known operation in abstract interpretation. In this paper we study the inverse operation, which we call complementation. Such an operation allows to systematically decompose domains; it provides a systematic way to design new abstract domains; it allows to simplify domain verification problems, like correctness proofs; and it yields space saving representations for domains. We show that the complement exists in most cases, and we apply complementation to two well known abstract domains, notably to the Cousot and Cousot's comportment domain for analysis of functional languages and to the complex domain Sharing for aliasing analysis of logic languages.

show abstract

Section: Introductionmentioning

confidence: 98%

Section: Functional Programming: Complementing Comportment Analysismentioning

confidence: 99%

Complementation in abstract interpretation

Cortesi

Filé

Ranzato

et al. 1997

ACM Trans. Program. Lang. Syst.

View full text Add to dashboard Cite

show abstract

“…Recall that a monotonic function is a formula such as x ∨ (y ∧ z). More exactly, a monotonic formula over set of variables X is any formula of the form ∨ n i=1 (∧Y i ) where Y i ⊆ X [Dart 1991]. Observe that each abstract clause arises from a clause p( x) :-b in the normalised program with a body that is a compound goal of the form b = e 1 , .…”

Section: Greatest Fixpoint Calculationmentioning

confidence: 99%

Inferring non-suspension conditions for logic programs with dynamic scheduling

Genaim

King

2008

ACM Trans. Comput. Logic

View full text Add to dashboard Cite

A logic program consists of a logic component and a control component. The former is a specification in predicate logic whereas the latter defines the order of sub-goal selection. The order of sub-goal selection is often controlled with delay declarations that specify that a sub-goal is to suspend until some condition on its arguments is satisfied. Reasoning about delay declarations is notoriously difficult for the programmer and it is not unusual for a program and a goal to reduce to a state that contains a sub-goal that suspends indefinitely. Suspending sub-goals are usually unintended and often indicate an error in the logic or the control. A number of abstract interpretation schemes have therefore been proposed for checking that a given program and goal cannot reduce to such a state. This paper considers a reversal of this problem, advocating an analysis that for a given program infers a class of goals that do not lead to suspension. This paper shows that this more general approach can have computational, implementational and user-interface advantages. In terms of user-interface, this approach leads to a lightweight point-and-click mode of operation in which, after directing the analyser at a file, the user merely has to inspect the results inferred by the analysis. In terms of implementation, the analysis can be straightforwardly realised as two simple fixpoint computations. In terms of computation, by modelling n! different schedulings of n sub-goals with a single Boolean function, it is possible to reason about the suspension behaviour of large programs. In particular, the analysis is fast enough to be applied repeatedly within the program development cycle. The paper also demonstrates that the method is precise enough to locate bugs in existing programs.

show abstract

“…We use the representation of an element F in Def as a conjunction of formulas, called definite clauses, of the form y1 /\ ... /\ Yn -+ x with n ~ 0 (see [8,2]). It has been recently shown in [4) that De/ characterizes the grounddependency information on V described by the domain Sharing.…”

Section: Def In Logical Formmentioning

confidence: 99%

“…The fragment .C of a first-order assertion language introduced in [13] (actually, a slight extension of this) is used. Logical descriptions of various abstract domains are given: Def [8] and Pos [14,15] for ground-dependency analysis; Sharing [10) and ASub [18) for aliasing analysis. Maximal factorizations for these domains are obtained by inspecting the structure of the assertions in the abstract domains, and they are used for analyzing and comparing the abstract domains.…”

Section: Introductionmentioning

confidence: 99%

Prime factorizations of abstract domains using first-order logic

Marchiori

1996

Algebraic and Logic Programming

View full text Add to dashboard Cite

Abstract. A methodology is introduced based on first-order logic, for the design and decomposition of abstract domains for abstract interpretation. First, an assertion language is chosen that describes the properties of interest. Next, abstract domains are defined to be suitably chosen sets of assertions. Finally, computer representations of abstract domains are defined in the expected way, as isomorphic copies of their specification in the assertion language. In order to decompose abstract domains, the notion of prime (conjunctive) factorization of sets of assertions is introduced. We illustrate this approach by considering typical abstract domains for ground-dependency and aliasing analysis in logic programming.

show abstract

On derived dependencies and connected databases

Cited by 37 publications

References 6 publications

Complementation in abstract interpretation

Complementation in abstract interpretation

Inferring non-suspension conditions for logic programs with dynamic scheduling

Prime factorizations of abstract domains using first-order logic

Contact Info

Product

Resources

About