Testing Identifiable Kernel P Systems Using an X-machine Approach

This paper presents a testing approach for kernel P systems (kP systems), based on the X-machine testing framework and the concept of cover automaton. The testing methodology ensures that the implementation conforms the speci cations, under certain conditions, such as the identi ably concept in the context of kernel P systems

Propositionalisation of multiple sequence alignments using probabilistic models

Multiple sequence alignments play a central role in Bioinformatics. Most alignment representations are designed to facilitate knowledge extraction by human experts. Additionally statistical models like Profile Hidden Markov Models are used as representations. They offer the advantage to provide sound, probabilistic scores. The basic idea we present in this paper is to use the structure of a Profile Hidden Markov Model for propositionalisation. This way we get a simple, extendable representation of multiple sequence alignments which facilitates further analysis by Machine Learning algorighms

Verification of Query Completeness over Processes [Extended Version]

Data completeness is an essential aspect of data quality, and has in turn a huge impact on the effective management of companies. For example, statistics are computed and audits are conducted in companies by implicitly placing the strong assumption that the analysed data are complete. In this work, we are interested in studying the problem of completeness of data produced by business processes, to the aim of automatically assessing whether a given database query can be answered with complete information in a certain state of the process. We formalize so-called quality-aware processes that create data in the real world and store it in the company's information system possibly at a later point.Comment: Extended version of a paper that was submitted to BPM 201

Refinement Calculus of Reactive Systems

Refinement calculus is a powerful and expressive tool for reasoning about sequential programs in a compositional manner. In this paper we present an extension of refinement calculus for reactive systems. Refinement calculus is based on monotonic predicate transformers, which transform sets of post-states into sets of pre-states. To model reactive systems, we introduce monotonic property transformers, which transform sets of output traces into sets of input traces. We show how to model in this semantics refinement, sequential composition, demonic choice, and other semantic operations on reactive systems. We use primarily higher order logic to express our results, but we also show how property transformers can be defined using other formalisms more amenable to automation, such as linear temporal logic (suitable for specifications) and symbolic transition systems (suitable for implementations). Finally, we show how this framework generalizes previous work on relational interfaces so as to be able to express systems with infinite behaviors and liveness properties

State-based and process-based value passing

State-based and process-based formalisms each come with their own distinct set of assumptions and properties. To combine them in a useful way it is important to be sure of these assumptions in order that the formalisms are combined in ways which have, or which allow, the intended combined properties. Consequently we cannot necessarily expect to take on state-based formalism and one process-based formalism and combine them and get something sensible, especially since the act of combining can have subtle consequences. Here we concentrate on value-passing, how it is treated in each formalism, and how the formalisms can be combined so as to preserve certain properties. Specifically, the aim is to take from the many process-based formalisms definitions that will best fit with our chosen stat-based formalism, namely Z, so that the fit is simple, has no unintended consequences and is as elegant as possible

Hierarchical Models for Relational Event Sequences

Interaction within small groups can often be represented as a sequence of events, where each event involves a sender and a recipient. Recent methods for modeling network data in continuous time model the rate at which individuals interact conditioned on the previous history of events as well as actor covariates. We present a hierarchical extension for modeling multiple such sequences, facilitating inferences about event-level dynamics and their variation across sequences. The hierarchical approach allows one to share information across sequences in a principled manner---we illustrate the efficacy of such sharing through a set of prediction experiments. After discussing methods for adequacy checking and model selection for this class of models, the method is illustrated with an analysis of high school classroom dynamics

Finite Model Finding for Parameterized Verification

In this paper we investigate to which extent a very simple and natural "reachability as deducibility" approach, originated in the research in formal methods in security, is applicable to the automated verification of large classes of infinite state and parameterized systems. The approach is based on modeling the reachability between (parameterized) states as deducibility between suitable encodings of states by formulas of first-order predicate logic. The verification of a safety property is reduced to a pure logical problem of finding a countermodel for a first-order formula. The later task is delegated then to the generic automated finite model building procedures. In this paper we first establish the relative completeness of the finite countermodel finding method (FCM) for a class of parameterized linear arrays of finite automata. The method is shown to be at least as powerful as known methods based on monotonic abstraction and symbolic backward reachability. Further, we extend the relative completeness of the approach and show that it can solve all safety verification problems which can be solved by the traditional regular model checking.Comment: 17 pages, slightly different version of the paper is submitted to TACAS 201