2,450 research outputs found
On Combining Linear-Based Strategies for Tabled Evaluation of Logic Programs
Tabled evaluation is a recognized and powerful technique that overcomes some
limitations of traditional Prolog systems in dealing with recursion and
redundant sub-computations. We can distinguish two main categories of tabling
mechanisms: suspension-based tabling and linear tabling. While suspension-based
mechanisms are considered to obtain better results in general, they have more
memory space requirements and are more complex and harder to implement than
linear tabling mechanisms. Arguably, the SLDT and DRA strategies are the two
most successful extensions to standard linear tabled evaluation. In this work,
we propose a new strategy, named DRS, and we present a framework, on top of the
Yap system, that supports the combination of all these three strategies. Our
implementation shares the underlying execution environment and most of the data
structures used to implement tabling in Yap. We thus argue that all these
common features allows us to make a first and fair comparison between these
different linear tabling strategies and, therefore, better understand the
advantages and weaknesses of each, when used solely or combined with the
others.Comment: 16 pages, 9 figures, International Conference on Logic Programming
(ICLP 2011
SLT-Resolution for the Well-Founded Semantics
Global SLS-resolution and SLG-resolution are two representative mechanisms
for top-down evaluation of the well-founded semantics of general logic
programs. Global SLS-resolution is linear for query evaluation but suffers from
infinite loops and redundant computations. In contrast, SLG-resolution resolves
infinite loops and redundant computations by means of tabling, but it is not
linear. The principal disadvantage of a non-linear approach is that it cannot
be implemented using a simple, efficient stack-based memory structure nor can
it be easily extended to handle some strictly sequential operators such as cuts
in Prolog.
In this paper, we present a linear tabling method, called SLT-resolution, for
top-down evaluation of the well-founded semantics. SLT-resolution is a
substantial extension of SLDNF-resolution with tabling. Its main features
include: (1) It resolves infinite loops and redundant computations while
preserving the linearity. (2) It is terminating, and sound and complete w.r.t.
the well-founded semantics for programs with the bounded-term-size property
with non-floundering queries. Its time complexity is comparable with
SLG-resolution and polynomial for function-free logic programs. (3) Because of
its linearity for query evaluation, SLT-resolution bridges the gap between the
well-founded semantics and standard Prolog implementation techniques. It can be
implemented by an extension to any existing Prolog abstract machines such as
WAM or ATOAM.Comment: Slight modificatio
Generalization Strategies for the Verification of Infinite State Systems
We present a method for the automated verification of temporal properties of
infinite state systems. Our verification method is based on the specialization
of constraint logic programs (CLP) and works in two phases: (1) in the first
phase, a CLP specification of an infinite state system is specialized with
respect to the initial state of the system and the temporal property to be
verified, and (2) in the second phase, the specialized program is evaluated by
using a bottom-up strategy. The effectiveness of the method strongly depends on
the generalization strategy which is applied during the program specialization
phase. We consider several generalization strategies obtained by combining
techniques already known in the field of program analysis and program
transformation, and we also introduce some new strategies. Then, through many
verification experiments, we evaluate the effectiveness of the generalization
strategies we have considered. Finally, we compare the implementation of our
specialization-based verification method to other constraint-based model
checking tools. The experimental results show that our method is competitive
with the methods used by those other tools. To appear in Theory and Practice of
Logic Programming (TPLP).Comment: 24 pages, 2 figures, 5 table
On Extending a Linear Tabling Framework to Support Batched Scheduling
Tabled evaluation is a recognized and powerful technique that overcomes some limitations of traditional Prolog systems in dealing with recursion and redundant sub-computations. During tabled execution, several decisions have to be made. These are determined by the scheduling strategy. Whereas a strategy can achieve very good performance for certain applications, for others it might add overheads and even lead to unacceptable inefficiency. The two most successful tabling scheduling strategies are local scheduling and batched scheduling. In previous work, we have developed a framework, on top of the Yap system, that supports the combination of different linear tabling strategies for local scheduling. In this work, we propose the extension of our framework, to support batched scheduling. In particular, we are interested in the two most successful linear tabling strategies, the DRA and DRE strategies. To the best of our knowledge, no single tabling Prolog system supports both strategies simultaneously for batched scheduling
Some improvements over the continuation call tabling implementation technique
Tabled evaluation has been proved an effective method to improve several aspeets of goal-oriented query evaluation, including termination and complexity. Several "native" implementations of tabled evaluation have been developed which offer good performance, but many of them need significant changes to the underlying Prolog implementation. More portable approaches, generally using program transformation, have been proposed but they often result in lower efficieney. We explore some techniques aimed at combining the best of these worlds, i.e., developing a portable and extensible implementation, with minimal modifications at the abstract machine level, and with reasonably good performance. Our preliminary results indÃcate promising results
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