Crowdsourcing for data management

The discovery of informative itemsets is a fundamental building block in data analytics and information retrieval. While the problem has been widely studied, only few solutions scale. This is particularly the case when (1) the data set is massive, calling for large-scale distribution, and/or (2) the length k of the informative itemset to be discovered is high. In this paper, we address the problem of parallel mining of maximally informative k-itemsets (miki) based on joint entropy. We propose PHIKS (Parallel Highly Informative \(\underline{K}\)-ItemSet), a highly scalable, parallel miki mining algorithm. PHIKS renders the mining process of large-scale databases (up to terabytes of data) succinct and effective. Its mining process is made up of only two efficient parallel jobs. With PHIKS, we provide a set of significant optimizations for calculating the joint entropies of miki having different sizes, which drastically reduces the execution time, the communication cost and the energy consumption, in a distributed computational platform. PHIKS has been extensively evaluated using massive real-world data sets. Our experimental results confirm the effectiveness of our proposal by the significant scale-up obtained with high itemsets length and over very large databases.     

A UTP semantics for Circus

Circus specifications define both data and behavioural aspects of systems using a combination of Z and CSP constructs. Previously, a denotational semantics has been given to Circus; however, a shallow embedding of Circus in Z, in which the mapping from Circus constructs to their semantic representation as a Z specification, with yet another language being used as a meta-language, was not useful for proving properties like the refinement laws that justify the distinguishing development technique associated with Circus. This work presents a final reference for the Circus denotational semantics based on Hoare and He’s Unifying Theories of Programming (UTP); as such, it allows the proof of meta-theorems about Circus including the refinement laws in which we are interested. Its correspondence with the CSP semantics is illustrated with some examples. We also discuss the library of lemmas and theorems used in the proofs of the refinement laws. Finally, we give an account of the mechanisation of the Circus semantics and of the mechanical proofs of the refinement laws.     

Least-change bidirectional model transformation with QVT-R and ATL

QVT Relations (QVT-R) is the standard language proposed by the OMG to specify bidirectional model transformations. Unfortunately, in part due to ambiguities and omissions in the original semantics, acceptance and development of effective tool support have been slow. Recently, the checking semantics of QVT-R has been clarified and formalized. In this article, we propose a QVT-R tool that complies to such semantics. Unlike any other existing tool, it also supports meta-models enriched with OCL constraints (thus avoiding returning ill-formed models) and proposes an alternative enforcement semantics that works according to the simple and predictable “principle of least change.” The implementation is based on an embedding of both QVT-R transformations and UML class diagrams (annotated with OCL) in Alloy, a lightweight formal specification language with support for automatic model finding via SAT solving. We also show how this technique can be applied to bidirectionalize ATL, a popular (but unidirectional) model transformation language.     

Slicing from formal semantics: Chisel—a tool for generic program slicing

We describe Chisel, a tool that synthesizes a program slicer directly from a given algebraic specification of a programming language operational semantics \(\mathcal {S}\). \(\mathcal {S}\) is assumed to be a rewriting logic specification, given in Maude, while the program is a ground term of this specification. Chisel takes \(\mathcal {S}\) and synthesizes language constructs, i.e., instructions, that produce features relevant for slicing, e.g., data dependency. We implement syntheses adjusted to each feature as model checking properties over an abstract representation of \(\mathcal {S}\). The syntheses results are used by a traditional interprocedural slicing algorithm that we parameterize by the synthesized language features. We present the tool on two language paradigms: high-level, imperative and low-level, assembly languages. Computing program slices for these languages allows for extracting traceability properties in standard compilation chains and makes our tool fitting for the validation of embedded system designs. Chisel’s slicing benchmark evaluation is based on benchmarks used in avionics.     

Language-Theoretic and Finite Relation Models for the (Full) Lambek Calculus

We prove completeness for some language-theoretic models of the full Lambek calculus and its various fragments. First we consider syntactic concepts and syntactic concepts over regular languages, which provide a complete semantics for the full Lambek calculus \({\mathbf {FL}}_\perp \). We present a new semantics we call automata-theoretic, which combines languages and relations via closure operators which are based on automaton transitions. We establish the completeness of this semantics for the full Lambek calculus via an isomorphism theorem for the syntactic concepts lattice of a language and a construction for the universal automaton recognizing the same language. Finally, we use automata-theoretic semantics to prove completeness of relation models of binary relations and finite relation models for the Lambek calculus without and with empty antecedents (henceforth: \(\mathbf L \) and \(\mathbf L1 \)), thus solving a problem left open by Pentus (Ann Pure Appl Log 75:179–213, 1995).     

The clock constraint specification language for building timed causality models

The uml Profile for Modeling and Analysis of Real-Time and Embedded (RTE) systems has recently been adopted by the OMG. Its Time Model extends the informal and simplistic Simple Time package proposed by Unified Modeling Language (UML2) and offers a broad range of capabilities required to model RTE systems including discrete/dense and chronometric/logical time. The Marte specification introduces a Time Structure inspired from several time models of the concurrency theory and proposes a new clock constraint specification language (ccsl) to specify, within the context of the uml, logical and chronometric time constraints. A semantic model in ccsl is attached to a (uml) model to give its timed causality semantics. In that sense, ccsl is comparable to the Ptolemy environment, in which directors give the semantics to models according to predefined models of computation and communication. This paper focuses on one historical model of computation of Ptolemy [Synchronous Data Flow (SDF)] and shows how to build SDF graphs by combining uml models and ccsl.     

A constrained $$\ell $$1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models

Identifying context-specific entity networks from aggregated data is an important task, arising often in bioinformatics and neuroimaging applications. Computationally, this task can be formulated as jointly estimating multiple different, but related, sparse undirected graphical models (UGM) from aggregated samples across several contexts. Previous joint-UGM studies have mostly focused on sparse Gaussian graphical models (sGGMs) and can’t identify context-specific edge patterns directly. We, therefore, propose a novel approach, SIMULE (detecting Shared and Individual parts of MULtiple graphs Explicitly) to learn multi-UGM via a constrained \(\ell \)1 minimization. SIMULE automatically infers both specific edge patterns that are unique to each context and shared interactions preserved among all the contexts. Through the \(\ell \)1 constrained formulation, this problem is cast as multiple independent subtasks of linear programming that can be solved efficiently in parallel. In addition to Gaussian data, SIMULE can also handle multivariate Nonparanormal data that greatly relaxes the normality assumption that many real-world applications do not follow. We provide a novel theoretical proof showing that SIMULE achieves a consistent result at the rate \(O(\log (Kp)/n_{tot})\). On multiple synthetic datasets and two biomedical datasets, SIMULE shows significant improvement over state-of-the-art multi-sGGM and single-UGM baselines (SIMULE implementation and the used datasets @https://github.com/QData/SIMULE).     

Efficient batch similarity join processing of social images based on arbitrary features

In this paper, we identify and solve a multi-join optimization problem for Arbitrary Feature-based social image Similarity JOINs(AFS-JOIN). Given two collections(i.e., R and S) of social images that carry both visual, spatial and textual(i.e., tag) information, the multiple joins based on arbitrary features retrieves the pairs of images that are visually, textually similar or spatially close from different users. To address this problem, in this paper, we have proposed three methods to facilitate the multi-join processing: 1) two baseline approaches(i.e., a naïve join approach and a maximal threshold(MT)-based), and 2) a Batch Similarity Join(BSJ) method. For the BSJ method, given m users’ join requests, they are first conversed and grouped into m″ clusters which correspond to m″ join boxes, where m > m″. To speedup the BSJ processing, a feature distance space is first partitioned into some cubes based on four segmentation schemes; the image pairs falling in the cubes are indexed by the cube tree index; thus BSJ processing is transformed into the searching of the image pairs falling in some affected cubes for m″ AFS-JOINs with the aid of the index. An extensive experimental evaluation using real and synthetic datasets shows that our proposed BSJ technique outperforms the state-of-the-art solutions.     

Group recommendation based on a bidirectional tensor factorization model

Capturing the preference of virtual groups that consist of a set of users with diversified preference helps recommend targeted products or services in social network platform. Existing strategies for capturing group preference are to directly aggregate individual preferences. Such methods model the preference formation of a group as a unidirectional procedure without considering the influence of the group on individual’s interest. In the context of social group, however, the preference formation is a bidirectional procedure because group preference and individual interest are interrelated. In addition, the influence of group on individuals is usually distinct among users. To address these issues, this paper models the group recommendation problem as a bidirectional procedure and proposes a Bidirectional Tensor Factorization model for Group Recommendation (BTF-GR) to capture the interaction between individual’s intrinsic interest and group influence. A Bayesian personalized ranking technique is employed to learn parameters of the proposed BTF-GR model. Empirical studies on two real-world data sets demonstrate that the proposed model outperforms the baseline algorithms such as matrix factorization for implicit feedback and Bayesian personalized ranking.     

Linguistic$$\leftrightarrow $$Rational Agents’ Semantics

We define and prove a formal semantics divided into two complementary interacting components: the strictly linguistic (i.e. linguistically marked) semantics, we call linguistic agent (LA), and the strictly logical and referential semantics, we call rational agent (RA). This Linguistic \(\leftrightarrow \) Rational Agents’ Semantics (LRA semantics) applies to Deep Dependency trees (DD-trees) or more generally, to discourses, i.e. sequences of DD-trees, and interprets them by functional structures we call Meaning Representation Structures (MRS), similar to the DRT, but interpreted very differently. LRA semantics incrementally interprets the discourses by minimal finite models, called proto-models, in a monotonic logic of the LA and checks the proto-models with respect to the classical models of the RA. The proto-model is considered as the linguistic sense of the discourse. We define in full detail the LA which, as we believe, must be universal. On the other hand, we don’t propose a particular RA. We only define the scheme of interaction between the two agents and the stimuli of the RA used by the LA. After all, every discourse has in LRA semantics the single meaning and the single sense for every Rational Agent used to interact with the Linguistic Agent.     

An executable formal semantics for UML-RT

We propose a formal semantics for UML-RT, a UML profile for real-time and embedded systems. The formal semantics is given by mapping UML-RT models into a language called kiltera, a real-time extension of the \(\pi \)-calculus. Previous attempts to formalize the semantics of UML-RT have fallen short by considering only a very small subset of the language and providing fundamentally incomplete semantics based on incorrect assumptions, such as a one-to-one correspondence between “capsules” and threads. Our semantics is novel in several ways: (1) it deals with both state machine diagrams and capsule diagrams; (2) it deals with aspects of UML-RT that have not been formalized before, such as thread allocation, service provision points, and service access points; (3) it supports an action language; and (4) the translation has been implemented in the form of a transformation from UML-RT models created with IBM’s RSA-RTE tool, into kiltera code. To our knowledge, this is the most comprehensive formal semantics for UML-RT to date.     

A compositional modelling and analysis framework for stochastic hybrid systems

The theory of hybrid systems is well-established as a model for real-world systems consisting of continuous behaviour and discrete control. In practice, the behaviour of such systems is also subject to uncertainties, such as measurement errors, or is controlled by randomised algorithms. These aspects can be modelled and analysed using stochastic hybrid systems. In this paper, we present HModest, an extension to the Modest modelling language—which is originally designed for stochastic timed systems without complex continuous aspects—that adds differential equations and inclusions as an expressive way to describe the continuous system evolution. Modest is a high-level language inspired by classical process algebras, thus compositional modelling is an integral feature. We define the syntax and semantics of HModest and show that it is a conservative extension of Modest that retains the compositional modelling approach. To allow the analysis of HModest models, we report on the implementation of a connection to recently developed tools for the safety verification of stochastic hybrid systems, and illustrate the language and the tool support with a set of small, but instructive case studies.     

Graph-based communication in Eden

We present a graph-based approach to the definition and creation of process topologies in the parallel Haskell extension Eden. Grace (Graph-based communication in Eden) allows the programmer to specify a network of processes as a graph, where the graph nodes represent processes and the edges represent communication channels. This simplifies the specification and creation of complex communication topologies. The main benefit of the Grace approach is the clean separation between coordination and computation. A special problem is the maintenance of type-safety. Runtime experiments show that Grace has a marginal overhead in comparison with traditional Eden code.     

PVS#: Streamlined Tacticals for PVS

The semantics of a proof language relies on the representation of the state of a proof after a logical rule has been applied. This information, which is usually meaningless from a logical point of view, is fundamental to describe the control mechanism of the proof search provided by the language. In this paper, we present a monadic datatype to represent the state information of a proof and we illustrate its use in the PVS theorem prover. We show how this representation can be used to design a new set of powerful tacticals for PVS, called PVS#, that have a simpler and clearer semantics compared to the semantics of standard PVS tacticals.     

Non-determinism in Gödel’s System <Emphasis Type="Italic">T</Emphasis>

The calculus T^? is a successor-free version of Gödel’s T. It is well known that a number of important complexity classes, like e.g. the classes logspace, \(\textsc{p}\), \(\textsc{linspace}\), \(\textsc{etime}\) and \(\textsc{pspace}\), are captured by natural fragments of T^? and related calculi. We introduce the calculus T^∽, which is a non-deterministic variant of T^?, and compare the computational power of T^∽ and T^?. First, we provide a denotational semantics for T^∽ and prove this semantics to be adequate. Furthermore, we prove that \(\textsc{linspace}\subseteq \mathcal {G}^{\backsim }_{0} \subseteq \textsc{linspace}\) and \(\textsc{etime}\subseteq \mathcal {G}^{\backsim }_{1} \subseteq \textsc{pspace}\) where \(\mathcal {G}^{\backsim }_{0}\) and \(\mathcal {G}^{\backsim }_{1}\) are classes of problems decidable by certain fragments of T^∽. (It is proved elsewhere that the corresponding fragments of T^? equal respectively \(\textsc{linspace}\) and \(\textsc{etime}\).) Finally, we show a way to interpret T^∽ in T^?.     

Translation-based approaches for solving disjunctive temporal problems with preferences

Disjunctive Temporal Problems (DTPs) with Preferences (DTPPs) extend DTPs with piece-wise constant preference functions associated to each constraint of the form l ≤ x ? y ≤ u, where x,y are (real or integer) variables, and l,u are numeric constants. The goal is to find an assignment to the variables of the problem that maximizes the sum of the preference values of satisfied DTP constraints, where such values are obtained by aggregating the preference functions of the satisfied constraints in it under a “max” semantic. The state-of-the-art approach in the field, implemented in the native DTPP solver Maxilitis, extends the approach of the native DTP solver Epilitis. In this paper we present alternative approaches that translate DTPPs to Maximum Satisfiability of a set of Boolean combination of constraints of the form l?x ? y?u, ? ∈{<,≤}, that extend previous work dealing with constant preference functions only. We prove correctness and completeness of the approaches. Results obtained with the Satisfiability Modulo Theories (SMT) solvers Yices and MathSAT on randomly generated DTPPs and DTPPs built from real-world benchmarks, show that one of our translation is competitive to, and can be faster than, Maxilitis (This is an extended and revised version of Bourguet et al. 2013).     

ReSpecT Nets: Towards an Analysis Methodology for ReSpecT Specifications

A key feature for infrastructures providing coordination services is the ability to define the behaviour of coordination abstractions according to the requirements identified at design-time. We take as a representative for this scenario the logic-based language ReSpecT (Reaction Specification Tuples), used to program the reactive behaviour of tuple centres. ReSpecT specifications are at the core of the engineering methodology underlying the TuCSoN infrastructure, and are therefore the “conceptual place” where formal methods can be fruitfully applied to guarantee relevant system properties.In this paper we introduce ReSpecT nets, a formalism that can be used to describe reactive behaviours that can succeed and fail, and that allows for an encoding to Petri nets with inhibitor arcs. ReSpecT nets are introduced to give a core model to a fragment of the ReSpecT language, and to pave the way for devising an analysis methodology including formal verification of safety and liveness properties. In particular, we provide a semantics to ReSpecT specifications through a mapping to ReSpecT nets. The potential of this approach for the analysis of ReSpecT specifications is discussed, presenting initial results for the analysis of safety properties.