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Knowledge Graph Embeddings (KGE) have become a quite popular class of models specifically devised to deal with ontologies and graph structure data, as they can implicitly encode statistical dependencies between entities and relations in a latent space. KGE techniques are particularly effective for the biomedical domain, where it is quite common to deal with large knowledge graphs underlying complex interactions between biological and chemical objects. Recently in the literature, the PharmKG dataset has been proposed as one of the most challenging knowledge graph biomedical benchmark, with hundreds of thousands of relational facts between genes, diseases and chemicals. Despite KGEs can scale to very large relational domains, they generally fail at representing more complex relational dependencies between facts, like logic rules, which may be fundamental in complex experimental settings. In this paper, we exploit logic rules to enhance the embedding representations of KGEs on the PharmKG dataset. To this end, we adopt Relational Reasoning Network (R2N), a recently proposed neural-symbolic approach showing promising results on knowledge graph completion tasks. An R2N uses the available logic rules to build a neural architecture that reasons over KGE latent representations. In the experiments, we show that our approach is able to significantly improve the current state-of-the-art on the PharmKG dataset. Finally, we provide an ablation study to experimentally compare the effect of alternative sets of rules according to different selection criteria and varying the number of considered rules.

Reaction Systems (RSs) are a successful computational framework inspired by biological systems. A RS pairs a set of entities with a set of reactions over them. Entities can be used to enable or inhibit each reaction, and are produced by reactions. Entities can also be provided by an external context. RS semantics is defined in terms of an (unlabelled) rewrite system: given the current set of entities, a rewrite step consists of the application of all and only the enabled reactions. In this paper we define, for the first time, a labelled transition system for RSs in the structural operational semantics (SOS) style. This is achieved by distilling a signature whose operators directly correspond to the ingredients of RSs and by defining some simple SOS inference rules for any such operator to define the behaviour of the RS in a compositional way. The rich information recorded in the labels allows us to define an assertion language to tailor behavioural equivalences on some specific properties or entities. The SOS approach is suited to drive additional enhancements of RSs along features such as quantitative measurements of entities and communication between RSs. The SOS rules have been also exploited to design a prototype implementation in logic programming., Comment: Part of WFLP 2020 pre-proceedings

Constraint Logic Programming (CLP) is a language scheme for combining two declarative paradigms: constraint solving and logic programming. Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact by telling and asking constraints in a shared store. In a previous paper, we developed a framework for dynamic slicing of CCP where the user first identifies that a (partial) computation is wrong. Then, she marks (selects) some parts of the final state corresponding to the data (constraints) and processes that she wants to study more deeply. An automatic process of slicing begins, and the partial computation is "depurated" by removing irrelevant information. In this paper we give two major contributions. First, we extend the framework to CLP, thus generalizing the previous work. Second, we provide an assertion language suitable for both, CCP and CLP, which allows the user to specify some properties of the computations in her program. If a state in a computation does not satisfy an assertion then some "wrong" information is identified and an automatic slicing process can start. This way we make one step further towards automatizing the slicing process. We show that our framework can be integrated with the previous semi-automatic one, giving the user more choices and flexibility. We show by means of examples and experiments the usefulness of our approach., Comment: Pre-proceedings paper presented at the 28th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2018), Frankfurt am Main, Germany, 4-6 September 2018 (arXiv:1808.03326)

Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact by telling and asking constraints (pieces of information) in a shared store. Some previous works have developed (approximated) declarative debuggers for CCP languages. However, the task of debugging concurrent programs remains difficult. In this paper we define a dynamic slicer for CCP and we show it to be a useful companion tool for the existing debugging techniques. Our technique starts by considering a partial computation (a trace) that shows the presence of bugs. Often, the quantity of information in such a trace is overwhelming, and the user gets easily lost, since she cannot focus on the sources of the bugs. Our slicer allows for marking part of the state of the computation and assists the user to eliminate most of the redundant information in order to highlight the errors. We show that this technique can be tailored to timed variants of CCP. We also develop a prototypical implementation freely available for making experiments., Comment: Pre-proceedings paper presented at the 26th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2016), Edinburgh, Scotland UK, 6-8 September 2016 (arXiv:1608.02534)

Timed Concurrent Constraint Programming (tcc) is a declarative model for concurrency offering a logic for specifying reactive systems, i.e. systems that continuously interact with the environment. The universal tcc formalism (utcc) is an extension of tcc with the ability to express mobility. Here mobility is understood as communication of private names as typically done for mobile systems and security protocols. In this paper we consider the denotational semantics for tcc, and we extend it to a "collecting" semantics for utcc based on closure operators over sequences of constraints. Relying on this semantics, we formalize a general framework for data flow analyses of tcc and utcc programs by abstract interpretation techniques. The concrete and abstract semantics we propose are compositional, thus allowing us to reduce the complexity of data flow analyses. We show that our method is sound and parametric with respect to the abstract domain. Thus, different analyses can be performed by instantiating the framework. We illustrate how it is possible to reuse abstract domains previously defined for logic programming to perform, for instance, a groundness analysis for tcc programs. We show the applicability of this analysis in the context of reactive systems. Furthermore, we make also use of the abstract semantics to exhibit a secrecy flaw in a security protocol. We also show how it is possible to make an analysis which may show that tcc programs are suspension free. This can be useful for several purposes, such as for optimizing compilation or for debugging.

The language Timed Concurrent Constraint (tccp) is the extension over time of the Concurrent Constraint Programming (cc) paradigm that allows us to specify concurrent systems where timing is critical, for example reactive systems. Systems which may have an infinite number of states can be specified in tccp. Model checking is a technique which is able to verify finite-state systems with a huge number of states in an automatic way. In the last years several studies have investigated how to extend model checking techniques to systems with an infinite number of states. In this paper we propose an approach which exploits the computation model of tccp. Constraint based computations allow us to define a methodology for applying a model checking algorithm to (a class of) infinite-state systems. We extend the classical algorithm of model checking for LTL to a specific logic defined for the verification of tccp and to the tccp Structure which we define in this work for modeling the program behavior. We define a restriction on the time in order to get a finite model and then we develop some illustrative examples. To the best of our knowledge this is the first approach that defines a model checking methodology for tccp.