Verification and falsification of programs with loops using predicate abstraction

Predicate abstraction is a major abstraction technique for the verification of software. Data is abstracted by means of Boolean variables, which keep track of predicates over the data. In many cases, predicate abstraction suffers from the need for at least one predicate for each iteration of a loop construct in the program. We propose to extract looping counterexamples from the abstract model, and to parametrise the simulation instance in the number of loop iterations. We present a novel technique that speeds up the detection of long counterexamples as well as the verification of programs with loops.     

On challenges of model transformation from UML to Alloy

The Unified Modeling Language (UML) is the de facto language used in the industry for software specifications. Once an application has been specified, Model Driven Architecture (MDA) techniques can be applied to generate code from such specifications. Since implementing a system based on a faulty design requires additional cost and effort, it is important to analyse the UML models at earlier stages of the software development lifecycle. This paper focuses on utilizing MDA techniques to deal with the analysis of UML models and identify design faults within a specification. Specifically, we show how UML models can be automatically transformed into Alloy which, in turn, can be automatically analysed by the Alloy Analyzer. The proposed approach relies on MDA techniques to transform UML models to Alloy. This paper reports on the challenges of the model transformation from UML class diagrams and OCL to Alloy. Those issues are caused by fundamental differences in the design philosophy of UML and Alloy. To facilitate better the representation of Alloy concepts in the UML, the paper draws on the lessons learnt and presents a UML profile for Alloy.     

Efficient moving horizon state and parameter estimation for SMB processes

In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm.     

Interactive volume exploration for feature detection and quantification in industrial CT data

This paper presents a novel method for interactive exploration of industrial CT volumes such as cast metal parts, with the goal of interactively detecting, classifying, and quantifying features using a visualization-driven approach. The standard approach for defect detection builds on region growing, which requires manually tuning parameters such as target ranges for density and size, variance, as well as the specification of seed points. If the results are not satisfactory, region growing must be performed again with different parameters. In contrast, our method allows interactive exploration of the parameter space, completely separated from region growing in an unattended pre-processing stage. The pre-computed feature volume tracks a feature size curve for each voxel over time, which is identified with the main region growing parameter such as variance. A novel 3D transfer function domain over (density, feature size, time) allows for interactive exploration of feature classes. Features and feature size curves can also be explored individually, which helps with transfer function specification and allows coloring individual features and disabling features resulting from CT artifacts. Based on the classification obtained through exploration, the classified features can be quantified immediately.     

On the Power of Las Vegas for One-Way Communication Complexity, OBDDs, and Finite Automata

The study of the computational power of randomized computations is one of the central tasks of complexity theory. The main goal of this paper is the comparison of the power of Las Vegas computation and deterministic respectively nondeterministic computation. We investigate the power of Las Vegas computation for the complexity measures of one-way communication, ordered binary decision diagrams, and finite automata.(i) For the one-way communication complexity of two-party protocols we show that Las Vegas communication can save at most one half of the deterministic one-way communication complexity. We also present a language for which this gap is tight.(ii) The result (i) is applied to show an at most polynomial gap between determinism and Las Vegas for ordered binary decision diagrams.(iii) For the size (i.e., the number of states) of finite automata we show that the size of Las Vegas finite automata recognizing a language L is at least the square root of the size of the minimal deterministic finite automaton recognizing L. Using a specific language we verify the optimality of this lower bound.     

Ontological query answering under expressive Entity-Relationship schemata

The Entity-Relationship (ER) model is a fundamental tool for database design, recently extended and employed in knowledge representation and reasoning due to its expressiveness and comprehensibility. We address the problem of answering conjunctive queries under constraints representing schemata expressed in an extended version of the Entity-Relationship model. This extended model, called ER⁺, comprises is-a constraints among entities and relationships, plus functional and mandatory participation constraints. In particular, it allows for arbitrary permutations of the roles in is-a among relationships. A key notion that ensures high tractability in ER⁺ schemata is separability, i.e., the absence of interaction between the functional participation constraints and the other constructs of ER⁺. We provide a precise syntactic characterization of separable ER⁺ schemata by means of a necessary and sufficient condition. We present a complete complexity analysis of the conjunctive query answering problem under separable ER⁺ schemata, and also under several sublanguages of ER⁺. We show that the addition of so-called negative constraints does not increase the complexity of query answering. With such constraints, our model properly generalizes the most widely adopted tractable ontology languages, including those in the DL-Lite family.     

Analysing quadratic effects of formative constructs by means of variance-based structural equation modelling

Together with the development of information systems research, there has also been increased interest in non-linear relationships between focal constructs. This article presents six Partial Least Squares-based approaches for estimating formative constructs’ quadratic effects. In addition, these approaches’ performance is tested by means of a complex Monte Carlo experiment. The experiment reveals significant and substantial differences between the approaches. In general, the performance of the hybrid approach as suggested by Wold (1982) is most convincing in terms of point estimate accuracy, statistical power, and prediction accuracy. The two-stage approach suggested by Chin et al (1996) showed almost the same performance; differences between it and the hybrid approach – although statistically significant – were unsubstantial. Based on these results, the article provides guidelines for the analysis of non-linear effects by means of variance-based structural equation modelling.     

Mobile robot localization using a self-organized visual environment representation

Owing to the upcoming applications in the field of service robotics mobile robots are currently receiving increasing attention in industry and the scientific community. Applications in the area of service robotics demand a high degree of system autonomy, which robots without learning capabilities will not be able to meet. Learning is required in the context of action models and appropriate perception procedures. In both areas flexible adaptivity is difficult to achieve especially when high bandwidth sensors (e.g. video cameras) - which are needed in the envisioned unstructured worlds - are used. This paper proposes a new methodology for image-based navigation using a self-organized visual representation of the environment. Self-organization leads to internal representations, which can be used by the robot, but are not transparent to the user. It is shown how this conceptual gap can be bridged.