Terrance Swift

XSB as an efficient deductive database engine

This paper describes the XSB system, and its use as an in-memory deductive database engine. XSB began from a Prolog foundation, and traditional Prolog systems are known to have serious deficiencies when used as database systems. Accordingly, XSB has a fundamental bottom-up extension, introduced through tabling (or memoing)[4], which makes it appropriate as an underlying query engine for deductive database systems. Because it eliminates redundant computation, the tabling extension makes XSB able to compute all modularly stratified datalog programs finitely and with polynomial data complexity. For non-stratified programs, a meta-interpreter with the same properties is provided. In addition XSB significantly extends and improves the indexing capabilities over those of standard Prolog. Finally, its syntactic basis in HiLog [2], lends it flexibility for data modelling. The implementation of XSB derives from the WAM [25], the most common Prolog engine. XSB inherits the WAMs efficiency and can take advantage of extensive compiler technology developed for Prolog. As a result, performance comparisons indicate that XSB is significantly faster than other deductive database systems for a wide range of queries and stratified rule sets. XSB is under continuous development, and version 1.3 is available through anonymous ftp.

Efficient Model Checking Using Tabled Resolution

We demonstrate the feasibility of using the XSB tabled logic programming system as a programmable fixed-point engine for implementing efficient local model checkers. In particular, we present XMC, an XSB-based local model checker for a CCS-like value-passing language and the alternation-free fragment of the modal mu-calculus. XMC is written in under 200 lines of XSB code, which constitute a declarative specification of CCS and the modal mu-calculus at the level of semantic equations.

Xsb: Extending prolog with tabled logic programming

The paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this are partly theoretical: tabling ensures termination and optimal known complexity for queries to a large class of programs. However, the overriding reasons are practical. TLP allows sophisticated programs to be written concisely and efficiently, especially when mechanisms such as tabled negation and call and answer subsumption are supported. As a result, TLP has now been used in a variety of applications from program analysis to querying over the semantic web. This paper provides a survey of TLP and its applications as implemented in the XSB Prolog, along with discussion of how XSB supports tabling with dynamically changing code, and in a multi-threaded environment.

XSB: A System for Effciently Computing WFS

The well-founded model provides a natural and robust semantics for logic programs with negative literals in rule bodies. We implemented the well-founded semantics in the SLG-WAM of XSB [19]. Performance results indicate that the overhead of delay and simplification to Prolog — or tabled — evaluations is minimal. To compute the well-founded semantics, the SLG-WAM adds to an efficient tabling engine for definite programs three operations — negative loop detection, delay and simplification — which serve to detect, to break and to resolve cycles through negation that might arise in evaluating normal programs. XSB is a full Prolog system that closely approximates the ISO standard; additionally, it supports a tight integration of tabled predicates with nontabled predicates.The well-founded model provides a natural and robust semantics for logic programs with negative literals in rule bodies. We implemented the well-founded semantics in the SLG-WAM of XSB 19]. Performance results indicate that the overhead of delay and simpliica-tion to Prolog | or tabled | evaluations is minimal. To compute the well-founded semantics, the SLG-WAM adds to an eecient tabling engine for deenite programs three operations | negative loop detection, delay and simpliication | which serve to detect, to break and to resolve cycles through negation that might arise in evaluating normal programs. XSB is a full Prolog system that closely approximates the ISO standard; additionally, it supports a tight integration of tabled predicates with nontabled predicates.

Efficient top-down computation of queries under the well-founded semantics

Abstract The well-founded model provides a natural and robust semantics for logic programs with negative literals in rule bodies. Although various procedural semantics have been proposed for query evaluation under the well-founded semantics, the practical issues of implementation for effective and efficient computation of queries have been rarely discussed. This paper investigates two major implementation issues of query evaluation under the well-founded semantics, namely, (a) to ensure that negative literals be resolved only after their positive counterparts have been completely evaluated, and (b) to detect and handle potential negative loops. We present efficient incremental algorithms for maintaining positive and negative dependencies among subgoals in a top-down evaluation. Both completely evaluated subgoals and potential negative loops are detected by inspecting the dependency information of a single subgoal. Our implementation can be viewed as an effective successor to SLDNF resolution, extending Prolog computation in a natural and smooth way.

Tabling for non-monotonic programming

Non‐monotonic extensions add power to logic programs. However, the main logic programming language, Prolog, is widely recognized as inadequate to implement these extensions due to its weak termination and complexity properties. By extending Prolog’s SLD resolution with tabling, Prolog can be improved in several ways. Tabling can allow a logic programming system to compute the well‐founded semantics for programs with bounded term depth, and to do so with polynomial data complexity. By exploiting these properties, tabling allows a variety of non‐monotonic extensions to be efficiently implemented, and used to solve practical problems. In this paper we describe tabling as it is implemented in the XSB system and show how it can be used to construct meta‐interpreters (or preprocessors) for two sample formalisms: the Well‐Founded Semantics with Explicit Negation, and Generalized Annotated Logic Programs. We also describe how non‐monotonic extensions are used in practical applications such as psychiatric diagnosis, extraction of information from poorly structured textual data, and model checking.

Abduction in well-founded semantics and generalized stable models via tabled dual programs

Abductive logic programming offers a formalism to declaratively express and solve problems in areas such as diagnosis, planning, belief revision and hypothetical reasoning. Tabled logic programming offers a computational mechanism that provides a level of declarativity superior to that of Prolog, and which has supported successful applications in fields such as parsing, program analysis, and model checking. In this paper we show how to use tabled logic programming to evaluate queries to abductive frameworks with integrity constraints when these frameworks contain both default and explicit negation. The result is the ability to compute abduction over well-founded semantics with explicit negation and answer sets. Our approach consists of a transformation and an evaluation method. The transformation adjoins to each objective literal

The PITA system: Tabling and answer subsumption for reasoning under uncertainty

O

Beyond Depth-First: Improving Tabled Logic Programs through Alternative Scheduling Strategies

in a program, an objective literal

Deduction in Ontologies via ASP

\hbox{\it not}(O)