Sharing is optimal

Cortesi, Agostino; Filé, Gilberto

doi:10.1016/s0743-1066(98)10026-2

Cited by 19 publications

(36 citation statements)

References 6 publications

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“…consistent renaming of variables) so as to provide a complete definition of the abstract semantics. Also note that these three operators have been proved to be the optimal approximations of the corresponding concrete operators (Cortesi & Filé, 1999). The j-self-union operator defined above is new.…”

Section: Examplementioning

confidence: 93%

“…For example, in the PhD thesis of Langen (Langen, 1990) this set is implicitly defined, for each clause being analyzed, as the finite set of variables occurring in that clause. A clearer approach has been introduced (Cortesi et al, 1994(Cortesi et al, , 1998 and also adopted (Bagnara et al, 1997(Bagnara et al, , 2001Cortesi & Filé, 1999), where the set of variables of interest is given explicitly as a component of the abstract domain. During the analysis process, this set is elastic.…”

Section: The Sharing Domainsmentioning

confidence: 99%

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Decomposing non-redundant sharing by complementation

Zaffanella

Hill

Bagnara

2002

Theory and Practice of Logic Programming

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Complementation, the inverse of the reduced product operation, is a technique for systematically finding minimal decompositions of abstract domains. Filé and Ranzato advanced the state of the art by introducing a simple method for computing a complement. As an application, they considered the extraction by complementation of the pair-sharing domain PS from the Jacobs and Langen's set-sharing domain SH . However, since the result of this operation was still SH , they concluded that PS was too abstract for this. Here, we show that the source of this result lies not with PS but with SH and, more precisely, with the redundant information contained in SH with respect to ground-dependencies and pair-sharing. In fact, a proper decomposition is obtained if the non-redundant version of SH , PSD, is substituted for SH . To establish the results for PSD, we define a general schema for subdomains of SH that includes PSD and Def as special cases. This sheds new light on the structure of PSD and exposes a natural though unexpected connection between Def and PSD. Moreover, we substantiate the claim that complementation alone is not sufficient to obtain truly minimal decompositions of domains. The right solution to this problem is to first remove redundancies by computing the quotient of the domain with respect to the observable behavior, and only then decompose it by complementation.

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Section: Examplementioning

confidence: 93%

Section: The Sharing Domainsmentioning

confidence: 99%

Decomposing non-redundant sharing by complementation

Zaffanella

Hill

Bagnara

2002

Theory and Practice of Logic Programming

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“…There have been much research in sharing analysis of logic programs [17,24,4,20,8,19,9,22,14,5] that have attempted to tame the computational aspects of this domain without compromising too much precision. One approach is reducing the number of groups that can possibly arise is due to Fecht [12] and Zaffanella et al [25] who use maximal elements to represent downward closed powersets of variables.…”

Section: Related Workmentioning

confidence: 99%

Lazy Set-Sharing Analysis

Li¹,

King²,

Lu³

2006

Functional and Logic Programming

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Abstract. Sharing analysis is widely deployed in the optimisation, specialisation and parallelisation of logic programs. Each abstract unification operation over the classic Jacobs and Langen domain involves the calculation of a closure operation that has exponential worst-case complexity. This paper explores a new tactic for improving performance: laziness. The idea is to compute partial sharing information eagerly and recover full sharing information lazily. The net result is an analysis that runs in a fraction of the time of the classic analysis and yet has comparable precision.

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“…Note that we do not impose the occur-check condition x / ∈ vars(t), since we have proved in [22] that this is not required to ensure correctness of the operations of Sharing and its derivatives. The following definitions are a simplification of the standard definitions for the Sharing domain [13,22,24] and assume that the set of variables of interest is VI . SH is ordered by subset inclusion.…”

Section: Preliminariesmentioning

confidence: 99%

Enhanced sharing analysis techniques: a comprehensive evaluation

Bagnara¹,

Zaffanella²,

Hill³

2005

Theory and Practice of Logic Programming

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Sharing, a domain due to D. Jacobs and A. Langen for the analysis of logic programs, derives useful aliasing information. It is well-known that a commonly used core of techniques, such as the standard integration of Sharing with freeness and linearity information, can significantly improve the precision of Sharing. However, a number of other proposals for refined domain combinations have been circulating for years. One feature that is common to these proposals is that they do not seem to have undergone a thorough experimental evaluation even with respect to the expected precision gains. In this paper, we discuss and/or experimentally evaluate: helping Sharing with definitely ground variables computed with Pos; the incorporation of explicit structural information into the domain of analysis; more sophisticated ways of integrating Sharing and Pos; the issue of reordering the bindings in the computation of the abstract mgu; an original proposal concerning the addition of a domain recording the set of variables that are deemed to be ground or free; a more refined way of using linearity to improve the analysis; the issue of whether tracking compoundness allows to compute more precise sharing information; and, finally, the recovery of hidden information in the combination of Sharing with the usual domain for freeness.

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Sharing is optimal

Cited by 19 publications

References 6 publications

Decomposing non-redundant sharing by complementation

Decomposing non-redundant sharing by complementation

Lazy Set-Sharing Analysis

Enhanced sharing analysis techniques: a comprehensive evaluation

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