Fixpoint Semantics Research Articles

Object-Oriented Fixpoint Programming with Datalog

Modern usages of Datalog exceed its original design purpose in scale and complexity. In particular, Datalog lacks abstractions for code organization and reuse, making programs hard to maintain. Is it possible to exploit abstractions and design patterns from object-oriented programming (OOP) while retaining a Datalog-like fixpoint semantics? To answer this question, we design a new OOP language called OODL with common OOP features: dynamic object allocation, object identity, dynamic dispatch, and mutation. However, OODL has a Datalog-like fixpoint semantics, such that recursive computations iterate until their result becomes stable. We develop two semantics for OODL: a fixpoint interpreter and a compiler that translates OODL to Datalog. Although the side effects found in OOP (object allocation and mutation) conflict with Datalog's fixpoint semantics, we can mostly resolve these incompatibilities through extensions of OODL. Within fixpoint computations, we employ immutable algebraic data structures (e.g. case classes in Scala), rather than relying on object allocation, and we introduce monotonically mutable data types (mono types) to enable a relaxed form of mutation. Our performance evaluation shows that the interpreter fails to solve fixpoint problems efficiently, whereas the compiled code exploits Datalog's semi-naïve evaluation.

Optimizing Nested Recursive Queries

Datalog is a declarative programming language that has gained popularity in various domains due to its simplicity, expressiveness, and efficiency. But "pure" Datalog is limited to monotone queries, and cannot be used in most practical applications. For that reason, newer systems are relaxing the language by allowing non-monotone queries to be freely combined with recursion. But by departing from the elegant fixpoint semantics of pure datalog, these systems often result in inefficient query execution, for example they perform redundant computations, or use redundant storage. In this paper, we propose Temporel, a system that allows recursion to be freely combined with non-monotone operators. Temporel optimizes the program by compiling it into a novel intermediate representation that we call TempoDL. Our experimental results show that our system outperforms a state-of-the-art Datalog engine as well as a vectorized and a compiled in-memory database system for a wide range of applications from machine learning to graph processing.

Verification of Safety for Synchronous-Reactive System Using Bounded Model Checking

Real-time embedded systems are increasingly applied in safety-critical areas, so guaranteeing the correctness of such systems by means of formal methods becomes particularly important. In this paper, we propose an optimized bounded model checking (BMC)-based formal verification approach for the verification of safety for synchronous-reactive (SR) models, which are often used to design systems with complicated control logic, especially the real-time embedded control systems. This method is based on the tackling of a series of challenging problems including the management of the logical clock, encoding of the contained ports, representation of the data types of ports, descriptions of behaviors of various components in a considered model, and formal consideration of the fixed-point semantics. We have implemented this proposed method in the prototype Ptolemy-Z3, and integrated this tool into the Ptolemy II environment. In addition, the experimental evaluation on 22 SR models has shown that our method performs better than the existing automatic verification method in Ptolemy II.

Notes on Models of (Partial) Kripke–Feferman Truth

This article investigates models of axiomatizations related to the semantic conception of truth presented by Kripke (J Philos 72(19):690–716, 1975), the so-called fixed-point semantics. Among the various proof systems devised as a proof-theoretic characterization of the fixed-point semantics, in recent years two alternatives have received particular attention: classical systems (i.e., systems based on classical logic) and nonclassical systems (i.e., systems based on some nonclassical logic). The present article, building on Halbach and Nicolai (J Philos Log 47(2):227–257, 2018), shows that there is a sense in which classical and nonclassical theories (in suitable variants) have the same models.

An Iterative Fixpoint Semantics for MKNF Hybrid Knowledge Bases with Function Symbols

Hybrid Knowledge Bases based on Lifschitz's logic of Minimal Knowledge with Negation as Failure are a successful approach to combine the expressivity of Description Logics and Logic Programming in a single language. Their syntax, defined by Motik and Rosati, disallows function symbols. In order to define a well-founded semantics for MKNF HKBs, Knorr et al. define a partition of the modal atoms occurring in it, called the alternating fixpoint partition. In this paper, we propose an iterated fixpoint semantics for HKBs with function symbols. We prove that our semantics extends Knorr et al.'s, in that, for a function-free HKBs, it coincides with its alternating fixpoint partition. The proposed semantics lends itself well to a probabilistic extension with a distribution semantic approach, which is the subject of future work.

The <img src=image/13426661_01.gif>-prime Radicals in Posets

A relation is a mathematical tool for describing set relationships. Relationships are common in databases and scheduling applications. Science and engineering are designed to help humans make better decisions. To make these choices, we must first understand human expectations, the outcomes of various options, and the degree of confidence. With all of these data, partial orders will be generated. In several fields of engineering and computer science, partial order and lattice theory are now widely used. To mention a few, they are used in cloud computing (vector clocks, global predicate detection), concurrency theory (pomsets, occurrence nets), programming language semantics (fixed-point semantics), and data mining (concept analysis). Other theoretical disciplines benefit from them as well, such as combinatorics, number theory, and group theory. Partially ordered sets emerge naturally when dealing with multidimensional systems of qualitative ordinal variables in social science, especially to solve ranking, prioritising, and assessment concerns. As an alternative to standard techniques, partial order theory and partially ordered sets can be used to generate composite indicators for evaluating well-being, quality of life, and multidimensional poverty. They can be applied in multi-criteria analysis or for decision-making purposes in the study of individual and social desires, including in social choice theory. They're also valuable in social network analysis, where they may be utilized to apply mathematics to explore network topologies and dynamics. The Hasse diagram method, for example, produces a partial order with multiple incomparabilities (lack of order) between pairs of items. This is a common problem in ranking studies, and it can often be avoided by combining object attributes that lead to a complete order. However, such a mix introduces subjectivity and prejudice into the rating process. This work discusses the notion of a <img src=image/13426661_01.gif>-prime radical of a partially ordered set with respect to ideal. In posets, we investigated the concept of <img src=image/13426661_01.gif>-primary ideals. It is investigated how to characterise <img src=image/13426661_01.gif>-primary ideals in relation to <img src=image/13426661_01.gif>-prime radicals. In addition, an ideal's <img src=image/13426661_01.gif>-primary decomposition is constructed.

Paraconsistent da Costa Weakening of Intuitionistic Negation: What does it mean?

In this paper we consider the systems of weakening of intuitionistic negation logic mZ, introduced in [1], [2], which are developed in the spirit of da Costa's approach. We take a particular attention on the philosophical considerations of the paraconsistent mZ logic w.r.t. the constructive semantics of the intuitionistic logic, and we show that mZ is a subintuitionistic logic. Hence, we present the relationship between intuitionistic and paraconsistent subintuitionistic negation used in mZ. Then we present a significant number of examples for this subintuitionistic and paraconsistent mZ logics: Logic Programming with Fiting's fixpoint semantics for paraconsistent weakening of 3-valued Kleene's and 4-valued Belnap's logics. Moreover, we provide a canonical construction of infinitary-valued mZ logics and, in particular, the paraconsistent weakening of standard Zadeh's fuzzy logic and of the Godel-Dummet t-norm intermediate logics.

Disjunctive logic programs, answer sets, and the cut rule

In Minker and Rajasekar (J Log Program 9(1):45–74, 1990), Minker proposed a semantics for negation-free disjunctive logic programs that offers a natural generalisation of the fixed point semantics for definite logic programs. We show that this semantics can be further generalised for disjunctive logic programs with classical negation, in a constructive modal-theoretic framework where rules are built from claims and hypotheses, namely, formulas of the form Box varphi and Diamond Box varphi where varphi is a literal, respectively, yielding a “base semantics” for general disjunctive logic programs. Model-theoretically, this base semantics is expressed in terms of a classical notion of logical consequence. It has a complete proof procedure based on a general form of the cut rule. Usually, alternative semantics of logic programs amount to a particular interpretation of nonclassical negation as “failure to derive.” The counterpart in our framework is to complement the original program with a set of hypotheses required to satisfy specific conditions, and apply the base semantics to the resulting set. We demonstrate the approach for the answer set semantics. The proposed framework is purely classical in mainly three ways. First, it uses classical negation as unique form of negation. Second, it advocates the computation of logical consequences rather than of particular models. Third, it makes no reference to a notion of preferred or minimal interpretation.

Some fixed point results and their applications on integral type contractive condition in fuzzy metric spaces

The role of Fuzzy topology in logic programming and algorithm has been recognized and applied on various programs to and more accurate result. In particular, topological methods are employed in order to obtain fixed point semantics for logic programs. In this paper, we prove some fixed point theorems in fuzzy metric spaces. As an application, some consequence theorems are given in support of our result.

Fixed-point models for paradoxical predicates

This paper introduces a new kind of fixed-point semantics, filling a gap within approaches to Liar-like paradoxes involving fixed-point models à la Kripke (1975). The four-valued models presented below, (i) unlike the three-valued, consistent fixed-point models defined in Kripke (1975), are able to differentiate between paradoxical and pathological-but-unparadoxical sentences, and (ii) unlike the four-valued, paraconsistent fixed-point models first studied in Visser (1984) and Woodruff (1984), preserve consistency and groundedness of truth. Keywords: Semantic Paradoxes · Fixed-point semantics · Many-valued logic · Kripke’s theory oftruth

Cut Elimination for Systems of Transparent Truth with Restricted Initial Sequents

The paper studies a cluster of systems for fully disquotational truth based on the restriction of initial sequents. Unlike well-known alternative approaches, such systems display both a simple and intuitive model theory and remarkable proof-theoretic properties. We start by showing that, due to a strong form of invertibility of the truth rules, cut is eliminable in the systems via a standard strategy supplemented by a suitable measure of the number of applications of truth rules to formulas in derivations. Next, we notice that cut remains eliminable when suitable arithmetical axioms are added to the system. Finally, we establish a direct link between cut-free derivability in infinitary formulations of the systems considered and fixed-point semantics. Noticeably, unlike what happens with other background logics, such links are established without imposing any restriction to the premises of the truth rules.

On the Costs of Classical Logic

This article compares classical (or KF-like) and nonclassical (or PKF-like) axiomatisations of the fixed-point semantics developed by Kripke (J Philos 72(19): 690–716, 1975). Following the line of investigation of Halbach and Nicolai (J Philos Logic 47(2): 227–257, 2018), we do not compare KF and PKF qua theories of truth simpliciter, but rather qua axiomatisations of the Kripkean conception of truth. We strengthen the central results of Halbach and Nicolai (2018) and Nicolai (Stud Log 106(1): 101–130, 2018), showing that, on the one hand, there is a stronger sense in which some variants of KF and some variants of PKF can be taken to be, truth-theoretically, equivalent. On the other hand, we show that this truth-theoretical equivalence is not preserved by some other variants of KF and PKF, arguing that the PKF variants are more adequate axiomatisations of the fixed-point semantics than the corresponding KF variants.

NONCLASSICAL TRUTH WITH CLASSICAL STRENGTH. A PROOF-THEORETIC ANALYSIS OF COMPOSITIONAL TRUTH OVER HYPE

AbstractQuestions concerning the proof-theoretic strength of classical versus nonclassical theories of truth have received some attention recently. A particularly convenient case study concerns classical and nonclassical axiomatizations of fixed-point semantics. It is known that nonclassical axiomatizations in four- or three-valued logics are substantially weaker than their classical counterparts. In this paper we consider the addition of a suitable conditional to First-Degree Entailment—a logic recently studied by Hannes Leitgeb under the label HYPE. We show in particular that, by formulating the theory PKF over HYPE, one obtains a theory that is sound with respect to fixed-point models, while being proof-theoretically on a par with its classical counterpart KF. Moreover, we establish that also its schematic extension—in the sense of Feferman—is as strong as the schematic extension of KF, thus matching the strength of predicative analysis.

Fixed point semantics for stream reasoning

Reasoning over streams of input data is an essential part of human intelligence. During the last decade stream reasoning has emerged as a research area within the AI-community with many potential applications. In fact, the increased availability of streaming data via services like Google and Facebook has raised the need for reasoning engines coping with data that changes at high rate. Recently, the rule-based formalism LARS for non-monotonic stream reasoning under the answer set semantics has been introduced. Syntactically, LARS programs are logic programs with negation incorporating operators for temporal reasoning, most notably window operators for selecting relevant time points. Unfortunately, by preselecting fixed intervals for the semantic evaluation of programs, the rigid semantics of LARS programs is not flexible enough to constructively cope with rapidly changing data dependencies. Moreover, we show that defining the answer set semantics of LARS in terms of FLP reducts leads to undesirable circular justifications similar to other ASP extensions. This paper fixes all of the aforementioned shortcomings of LARS. More precisely, we contribute to the foundations of stream reasoning by providing an operational fixed point semantics for a fully flexible variant of LARS and we show that our semantics is sound and constructive in the sense that answer sets are derivable bottom-up and free of circular justifications.

Debugging Large-scale Datalog

Logic programming languages such as Datalog have become popular as Domain Specific Languages (DSLs) for solving large-scale, real-world problems, in particular, static program analysis and network analysis. The logic specifications that model analysis problems process millions of tuples of data and contain hundreds of highly recursive rules. As a result, they are notoriously difficult to debug. While the database community has proposed several data provenance techniques that address the Declarative Debugging Challenge for Databases, in the cases of analysis problems, these state-of-the-art techniques do not scale. In this article, we introduce a novel bottom-up Datalog evaluation strategy for debugging: Our provenance evaluation strategy relies on a new provenance lattice that includes proof annotations and a new fixed-point semantics for semi-naïve evaluation. A debugging query mechanism allows arbitrary provenance queries, constructing partial proof trees of tuples with minimal height. We integrate our technique into Soufflé, a Datalog engine that synthesizes C++ code, and achieve high performance by using specialized parallel data structures. Experiments are conducted with D OOP /DaCapo, producing proof annotations for tens of millions of output tuples. We show that our method has a runtime overhead of 1.31× on average while being more flexible than existing state-of-the-art techniques.

HR-SQL: Extending SQL with hypothetical reasoning and improved recursion for current database systems

In this work we present a formalization, backed with a contrasted implementation, of a relational database language (called HR-SQL) that extends SQL in two aspects. On the one hand, including non-linear and mutual recursion. On the other hand, including hypothetical relations and queries. Regarding expressiveness, HR-SQL allows a novel form of hypothetical reasoning, completely integrated with recursive definitions. In addition, aggregate functions are added. Regarding formalization, the extended language is founded on a stratified fixpoint semantics based on logic programming techniques. We include results of the existence of such fixpoints. An algorithm that transforms a database containing hypothetical definitions into an equivalent one without hypothesis and its correctness proof are presented. Regarding the implementation, we introduce here a system that incorporates the aforementioned benefits and enhances former implementations in several areas. The current HR-SQL system is targeted to several state-of-the-art relational database systems, and could be used with any SQL-based system with minor modifications in the implementation.

Scaling-up reasoning and advanced analytics on BigData

AbstractBigDatalog is an extension of Datalog that achieves performance and scalability on both Apache Spark and multicore systems to the point that its graph analytics outperform those written in GraphX. Looking back, we see how this realizes the ambitious goal pursued by deductive database researchers beginning 40 years ago: this is the goal of combining the rigor and power of logic in expressing queries and reasoning with the performance and scalability by which relational databases managed BigData. This goal led to Datalog which is based on Horn Clauses like Prolog but employs implementation techniques, such as semi-naïve fixpoint and magic sets, that extend the bottom-up computation model of relational systems, and thus obtain the performance and scalability that relational systems had achieved, as far back as the 80s, using data-parallelization on shared-nothing architectures. But this goal proved difficult to achieve because of major issues at (i) the language level and (ii) at the system level. The paper describes how (i) was addressed by simple rules under which the fixpoint semantics extends to programs using count, sum and extrema in recursion, and (ii) was tamed by parallel compilation techniques that achieve scalability on multicore systems and Apache Spark. This paper is under consideration for acceptance in Theory and Practice of Logic Programming.

Revision Without Revision Sequences: Self-Referential Truth

The model of self-referential truth presented in this paper, named Revision-theoretic supervaluation, aims to incorporate the philosophical insights of Gupta and Belnap’s Revision Theory of Truth into the formal framework of Kripkean fixed-point semantics. In Kripke-style theories the final set of grounded true sentences can be reached from below along a strictly increasing sequence of sets of grounded true sentences: in this sense, each stage of the construction can be viewed as an improvement on the previous ones. I want to do something similar replacing the Kripkean sets of grounded true sentences with revision-theoretic sets of stable true sentences. This can be done by defining a monotone operator through a variant of van Fraassen’s supervaluation scheme which is simply based on ω-length iterations of the Tarskian operator. Clearly, all virtues of Kripke-style theories are preserved, and we can also prove that the resulting set of “grounded” true sentences shares some nice features with the sets of stable true sentences which are provided by the usual ways of formalising revision. What is expected is that a clearer philosophical content could be associated to this way of doing revision; hopefully, a content directly linked with the insights underlying finite revision processes.

Foundations for natural proofs and quantifier instantiation

We give foundational results that explain the efficacy of heuristics used for dealing with quantified formulas and recursive definitions. We develop a framework for first order logic (FOL) over an uninterpreted combination of background theories. Our central technical result is that systematic term instantiation is complete for a fragment of FOL that we call safe . Coupled with the fact that unfolding recursive definitions is essentially term instantiation and with the observation that heap verification engines generate verification conditions in the safe fragment explains the efficacy of verification engines like natural proofs that resort to such heuristics. Furthermore, we study recursive definitions with least fixpoint semantics and show that though they are not amenable to complete procedures, we can systematically introduce induction principles that in practice bridge the divide between FOL and FOL with recursive definitions.

Fixpoint semantics for active integrity constraints

Active integrity constraints (AICs) constitute a formalism to associate with a database not just the constraints it should adhere to, but also how to fix the database in case one or more of these constraints are violated. The intuitions regarding which repairs are “good” given such a description are closely related to intuitions that live in various areas of non-monotonic reasoning, such as logic programming and autoepistemic logic.In this paper, we apply approximation fixpoint theory, an abstract, algebraic framework designed to unify semantics of non-monotonic logics, to the field of AICs. This results in a new family of semantics for AICs. We study properties of our new semantics and relationships to existing semantics. In particular, we argue that two of the newly defined semantics stand out. Grounded repairs have a simple definition that is purely based on semantic principles that semantics for AICs should adhere to. And, as we show, they coincide with the intended interpretation of AICs on many examples. The second semantics of interest is the AFT-well-founded semantics: it is a computationally cheap semantics that provides upper and lower bounds for many other classes of repairs.