Technological progress in Answer Set Programming (ASP) has been stimulated by the use of common standards, such as the ASP-Core-2 language. While ASP has its roots in nonmonotonic reasoning, efforts have also been made to reconcile ASP with classical first-order (FO) logic. This has resulted in the development of FO(·), an expressive extension of FO, which allows ASP-like problem solving in a purely classical setting. This language may be more accessible to domain experts already familiar with FO and may be easier to combine with other formalisms that are based on classical logic. It is supported by the IDP inference system, which has successfully competed in a number of ASP competitions. Here, however, technological progress has been hampered by the limited number of systems that are available for FO(·). In this paper, we aim to address this gap by means of a translation tool that transforms an FO(·) specification into ASP-Core-2, thereby allowing ASP-Core-2 solvers to be used as solvers for FO(·) as well. We present experimental results to show that the resulting combination of our translation with an off-the-shelf ASP solver is competitive with the IDP system as a way of solving problems formulated in FO(·).

This paper looks at logic programming with three kinds of negation: default, weak and strict negations. A 3-valued logic model theory is discussed for logic programs with three kinds of negation. The procedure is constructed for negations so that a soundness of the procedure is guaranteed in terms of 3-valued logic model theory.

An open ended list is a well known data structure in Prolog programs. It is frequently used to represent a value changing over time, while this value is referred to from several places in the data structure of the application. A weak point in this technique is that the time complexity is linear in the number of updates to the value represented by the open ended list. In this programming pearl we present a variant of the open ended list, namely an open ended tree, with an update and access time complexity logarithmic in the number of updates to the value.

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.

Even though the core of the Prolog programming language has been standardized by ISO since 1995, it remains difficult to write complex Prolog programs that can run unmodified on multiple Prolog implementations. Indeed, implementations sometimes deviate from the ISO standard and the standard itself fails to cover many features that are essential in practice. Most Prolog applications thus have to rely on nonstandard features, often making them dependent on one particular Prolog implementation and incompatible with others. We examine one such Prolog application: ProB, which has been developed for over 20 years in SICStus Prolog. The article describes how we managed to refactor the codebase of ProB to also support SWI-Prolog, with the goal of verifying ProB’s results using two independent toolchains. This required a multitude of adjustments, ranging from extending the SICStus emulation in SWI-Prolog on to better modularizing the monolithic ProB codebase. We also describe notable compatibility issues and other differences that we encountered in the process, and how we were able to deal with them with few major code changes.

In temporal extensions of answer set programming (ASP) based on linear time, the behavior of dynamic systems is captured by sequences of states. While this representation reflects their relative order, it abstracts away the specific times associated with each state. However, timing constraints are important in many applications like, for instance, when planning and scheduling go hand in hand. We address this by developing a metric extension of linear-time temporal equilibrium logic, in which temporal operators are constrained by intervals over natural numbers. The resulting Metric Equilibrium Logic (MEL) provides the foundation of an ASP-based approach for specifying qualitative and quantitative dynamic constraints. To this end, we define a translation of metric formulas into monadic first-order formulas and give a correspondence between their models in MEL and Monadic Quantified Equilibrium Logic, respectively. Interestingly, our translation provides a blue print for implementation in terms of ASP modulo difference constraints.

Constraint Handling Rules (CHR) is both an effective concurrent declarative programming language and a versatile computational logic formalism. In CHR, guarded reactive rules rewrite a multi-set of constraints. Concurrency is inherent, since rules can be applied to the constraints in parallel. In this comprehensive survey, we give an overview of the concurrent, parallel as well as distributed CHR semantics, standard and more exotic, that have been proposed over the years at various levels of refinement. These semantics range from the abstract to the concrete. They are related by formal soundness results. Their correctness is proven as a correspondence between parallel and sequential computations. On the more practical side, we present common concise example CHR programs that have been widely used in experiments and benchmarks. We review parallel and distributed CHR implementations in software as well as hardware. The experimental results obtained show a parallel speed-up for unmodified sequential CHR programs. The software implementations are available online for free download and we give the web links. Due to its high level of abstraction, the CHR formalism can also be used to implement and analyse models for concurrency. To this end, the Software Transaction Model, the Actor Model, Colored Petri Nets and the Join-Calculus have been faithfully encoded in CHR. Finally, we identify and discuss commonalities of the approaches surveyed and indicate what problems are left open for future research.

Domain-specific languages (DSLs) are routinely created to simplify difficult or specialized programming tasks. They expose useful abstractions and design patterns in the form of language constructs, provide static semantics to eagerly detect misuse of these constructs, and dynamic semantics to completely define how language constructs interact. However, implementing and composing DSLs is a non-trivial task, and there is a lack of tools and techniques.

We address this problem by presenting a complete module system over LP for DSL construction, reuse, and composition. LP is already useful for DSL design, because it supports executable language specifications using notations familiar to language designers. We extend LP with a module system that is simple (with a few concepts), succinct (for key DSL specification scenarios), and composable (on the level of languages, compilers, and programs). These design choices reflect our use of LP for industrial DSL design. Our module system has been implemented in the formula language, and was used to build key Windows 8 device drivers via DSLs. Though we present our module system as it actually appears in our formula language, our emphasis is on concepts adaptable to other LP languages.

As an invited contributor to this Festschrift honoring Alain Colmerauer, I feel compelled to give not only an account of his main research contributions, but also of my perspective on the motivations behind them. I hope that this will provide the reader with a glimpse of how a focused, tenacious, rigorous, and inventive mind like Alain's picks research problems and proceeds to solve them. The history of Prolog, the language that remains one of Alain's major accomplishments, is well documented. His paper on the ‘Birth of Prolog,’ co-authored with Philippe Roussel (Colmerauer & Roussel, 1970), is a highly recommended account of the circumstances that led to the development of Prolog. Bob Kowalski (1988) presents his views of the early history of Prolog from the automatic theorem proving perspective. Finally, my own paper on the topic (Cohen, 1988) contains material complementing Alain's and Bob's narratives. Instead of recasting already-available historical material, I have opted to present here a more personal account of Alain's contributions, acknowledging in advance the individual bias inherent in such an accounting of long-past events.

Meseguer's rewriting logic and the rewriting logic CRWL are two well-known approaches to rewriting as logical deduction that, despite some clear similarities, were designed with different objectives. Here we study the relationships between them, both at a syntactic and at a semantic level. Even though it is not possible to establish an entailment system map between them, both can be naturally simulated in each other. Semantically, there is no embedding between the corresponding institutions. Along the way, the notions of entailment and satisfaction in Meseguer's rewriting logic are generalized.

We study here schedulers for a class of rules that naturally arise in the context of rule-based constraint programming. We systematically derive a scheduler for them from a generic iteration algorithm of Apt (2000). We apply this study to so-called membership rules of Apt and Monfroy (2001). This leads to an implementation that yields a considerably better performance for these rules than their execution as standard CHR rules. Finally, we show how redundant rules can be identified and how appropriately reduced sets of rules can be computed.

We consider disjunctive logic programs without function symbols but with existential quantification in rule heads, under the semantics of general stable models. There are at least two interesting prospects in these programs. The first is that a program can be made more succinct by using existential variables, and the second is on the potential in representing defeasible ontological knowledge by these logic programs. This paper studies some of the properties of these programs. First, we show a simple yet intuitive definition of stable models for these programs that does not resort to second-order logic. Second, the stable models of these programs can be characterized by an extension of progression for disjunctive programs, which provides a native characterization of justification for stable models. We then study the decidability issue. While the stable model existence problem for safe disjunctive programs is decidable, with existential quantification allowed in rule heads the problem becomes undecidable. We identify an interesting decidable fragment by exploring a new notion of stratification over existential quantification.

Answer set programming is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing different knowledge representation formalisms. Frequently, several related and yet substantially different answer set programs exist for a given problem. Sometimes these encodings may display significantly different performance. Uncovering precise formal links between these programs is often important and yet far from trivial. This paper presents formal results carefully relating a number of interesting program rewritings. It also provides the proof of correctness of system projector concerned with automatic program rewritings for the sake of efficiency.

Prolog's very useful expressive power is not captured by traditional logic programming semantics, due mainly to the cut and goal and clause order. Several alternative semantics have been put forward, exposing operational details of the computation state. We propose instead to redesign Prolog around structured alternatives to the cut and clauses, keeping the expressive power and computation model but with a compositional denotational semantics over much simpler states—just variable bindings. This considerably eases reasoning about programs, by programmers and tools such as a partial evaluator, with safe unfolding of calls through predicate definitions. An if-then-else across clauses replaces most uses of the cut, but the cut's full power is achieved by an until construct. Disjunction, conjunction and until, along with unification, are the primitive goal types with a compositional semantics yielding sequences of variable-binding solutions. This extends to programs via the usual technique of a least fixpoint construction. A simple interpreter for Prolog in the alternative language, and a definition of until in Prolog, establish the identical expressive power of the two languages. Many useful control constructs are derivable from the primitives, and the semantic framework illuminates the discussion of alternative ones. The formalisation rests on a term language with variable abstraction as in the λ-calculus. A clause is an abstraction on the call arguments, a continuation, and the local variables. It can be inclusive or exclusive, expressing a local case bound to a continuation by either a disjunction or an if-then-else. Clauses are open definitions, composed (and closed) with simple functional application β-reduction). This paves the way for a simple account of flexible module composition mechanisms. Cube, a concrete language with the exposed principles, has been implemented on top of a Prolog engine and successfully used to build large real-world applications.

A plethora of approaches have been proposed for joint entity-relation (ER) extraction. Most of these methods largely depend on a large amount of manually annotated training data. However, manual data annotation is time-consuming, labor-intensive, and error-prone. Human beings learn using both data (through induction) and knowledge (through deduction). Answer Set Programming (ASP) has been a widely utilized approach for knowledge representation and reasoning that is elaboration tolerant and adept at reasoning with incomplete information. This paper proposes a new approach, ASP-enhanced Entity-Relation extraction (ASPER), to jointly recognize entities and relations by learning from both data and domain knowledge. In particular, ASPER takes advantage of the factual knowledge (represented as facts in ASP) and derived knowledge (represented as rules in ASP) in the learning process of neural network models. We have conducted experiments on two real datasets and compare our method with three baselines. The results show that our ASPER model consistently outperforms the baselines.

The development of complex software requires tools promoting fail-fast approaches, so that bugs and unexpected behavior can be quickly identified and fixed. Tools for data validation may save the day of computer programmers. In fact, processing invalid data is a waste of resources at best, and a drama at worst if the problem remains unnoticed and wrong results are used for business. Answer Set Programming (ASP) is not an exception, but the quest for better and better performance resulted in systems that essentially do not validate data. Even under the simplistic assumption that input/output data are eventually validated by external tools, invalid data may appear in other portions of the program, and go undetected until some other module of the designed software suddenly breaks. This paper formalizes the problem of data validation for ASP programs, introduces a language to specify data validation, and presents valasp, a tool to inject data validation in ordinary programs. The proposed approach promotes fail-fast techniques at coding time without imposing any lag on the deployed system if data are pretended to be valid. Validation can be specified in terms of statements using YAML, ASP and Python. Additionally, the proposed approach opens the possibility to use ASP for validating data of imperative programming languages.

We address the problem of verifying clique avoidance in the TTP protocol. TTP allows several stations embedded in a car to communicate. It has many mechanisms to ensure robustness to faults. In particular, it has an algorithm that allows a station to recognize itself as faulty and leave the communication. This algorithm must satisfy the crucial ‘non-clique’ property: it is impossible to have two or more disjoint groups of stations communicating exclusively with stations in their own group. In this paper, we propose an automatic verification method for an arbitrary number of stations $N$ and a given number of faults $k$. We give an abstraction that allows to model the algorithm by means of unbounded (parametric) counter automata. We have checked the non-clique property on this model in the case of one fault, using the ALV tool as well as the LASH tool.

Epistemic Logic Programs (ELPs) extend Answer Set Programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems for ELPs. In practice, ELPs are often written in a modular way, where each module interacts with other modules by accepting sets of facts as input, and passing on sets of facts as output. An interesting question then presents itself: under which conditions can such a module be replaced by another one without changing the outcome, for any set of input facts? This problem is known as uniform equivalence, and has been studied extensively for ASP. For ELPs, however, such an investigation is, as of yet, missing. In this paper, we therefore propose a characterization of uniform equivalence that can be directly applied to the language of state-of-the-art ELP solvers. We also investigate the computational complexity of deciding uniform equivalence for two ELPs, and show that it is on the third level of the polynomial hierarchy.

Abstract solvers are a method to formally analyze algorithms that have been profitably used for describing, comparing and composing solving techniques in various fields such as Propositional Satisfiability (SAT), Quantified SAT, Satisfiability Modulo Theories, Answer Set Programming (ASP), and Constraint ASP.

In this paper, we design, implement and test novel abstract solutions for cautious reasoning tasks in ASP. We show how to improve the current abstract solvers for cautious reasoning in ASP with new techniques borrowed from backbone computation in SAT, in order to design new solving algorithms. By doing so, we also formally show that the algorithms for solving cautious reasoning tasks in ASP are strongly related to those for computing backbones of Boolean formulas. We implement some of the new solutions in the ASP solver wasp and show that their performance are comparable to state-of-the-art solutions on the benchmark problems from the past ASP Competitions.