Abstract. We propose a modular, assertion-based system for verification and debugging of large logic programs, together with several interesting models for checking assertions statically in modular programs, each with different characteristics and representing different trade-offs. Our proposal is a modular and multivariant extension of our previously proposed abstract assertion checking model and we also report on its implementation in the CiaoPP system. In our approach, the specification of the program, given by a set of assertions, may be partial, instead of the complete specification required by traditional verification systems. Also, the system can deal with properties which cannot always be determined at compile-time. As a result, the proposed system needs to work with safe approximations: all assertions proved correct are guaranteed to be valid and all errors actual errors. The use of modular, context-sensitive static analyzers also allows us to introduce a new distinction between assertions checked in a particular context or checked in general.

Abstract. Live heap space analyses have so far been concerned with the standard sequential programming model. However, that model is not very well suited for embedded real-time systems, where fragments of code execute concurrently and in orders determined by periodic and sporadic events. Schedulability analysis has shown that the programming model of real-time systems is not fundamentally in conflict with static predictability, but in contrast to accumulative properties like time, live heap space usage exhibits a very state-dependent behavior that renders direct application of schedulability analysis techniques unsuitable. In this paper we propose an analysis of live heap space upper bounds for real-time systems based on an accurate prediction of task execution orders. The key component of our analysis is the construction of a nondeterministic finite state machine capturing all task executions that are legal under given timing assumptions. By adding heap usage information inferred for each sequential task, our analysis finds an upper bound on the inter-task heap demands as the solution to an integer linear programming problem. Values so obtained are suitable inputs to other analyses depending on the size of a system's persistent state, such as running time prediction for a concurrent tracing garbage collector.

In this paper, a nonlinear three-degrees-of-freedom dynamical system consisting of a variable-length pendulum mass attached by a massless spring to the forced slider is investigated. Numerical solution is preceded by application of Euler-Lagrange equation. Various techniques like time histories, phase planes, Poincaré maps and resonance plots are used to observe and identify the system responses. The results show that the variable-length spring pendulum suspended from the periodically forced slider can exhibit quasi-periodic, and in a resonance state, even chaotic motions. It was concluded that near the resonance the influence of coupling of bodies on the system dynamics can lead to unpredictable dynamical behavior.

Regular types are a powerful tool for computing very precise descriptive types for logic programs. However, in the context of reallife, modular Prolog programs, the accurate results obtained by regular types often come at the price of efficiency. In this paper we propose a combination of techniques aimed at improving analysis efficiency in this context. As a first technique we allow optionally reducing the accuracy of inferred types by using only the types defined by the user or present in the libraries. We claim that, for the purpose of verifying type signatures given in the form of assertions the precision obtained using this approach is sufficient, and show that analysis times can be reduced significantly. Our second technique is aimed at dealing with situations where we would like to limit the amount of reanalysis performed, especially for library modules. Borrowing some ideas from polymorphic type systems, we show how to solve the problem by admitting parameters in type specifications. This allows us to compose new call patterns with some precomputed analysis info without losing any information. We argue that together these two techniques contribute to the practical and scalable analysis and verification of types in Prolog programs.

This paper introduces a framework of parametric descriptive directional types for Constraint Logic Programming (CLP). It proposes a method for locating type errors in CLP programs, and presents a prototype debugging tool. The main technique used is checking correctness of programs w.r.t. type specifications. The approach is based on a generalization of known methods for proving the correctness of logic programs to the case of parametric specifications. Set constraint techniques are used for formulating and checking verification conditions for (parametric) polymorphic type specifications. The specifications are expressed in a parametric extension of the formalism of term grammars. The soundness of the method is proved, and the prototype debugging tool supporting the proposed approach is illustrated on examples. The paper is a substantial extension of the previous work by the same authors concerning monomorphic directional types.

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<p>A free-burning arc experiment was performed in a gas mixture composed of CO2 /O2 /C5F10O (85% / 10% / 5%). An optical emission spectroscopy diagnostic was developed to obtain spatially resolved arc spectra at a high frame-rate. Spectral measurements are compared with simulated spectra to estimate arc parameters including temperature and composition. These techniques are used to characterize the arc and its associated electrode jets over a range of conditions, in order to study the influence of ablated Cu/W on arc characteristics. The observed spectra indicate that the ablation of the contact tip primarily occurs through vaporization rather than the expulsion of droplets. The metal vapor content of the arc is investigated as the arc driving current is varied, and a transition threshold for increased ablation at electrode current densities above 50A/mm² is determined. The expansion angle of the electrode jet is estimated from the concentration of metal vapor in the arcing region at different axial positions, using a basic conical expansion model. The dependence of the measured voltage on the arc composition is examined, and a positive correlation between Cu content and arc voltage is identified. This trend is attributed to the higher emissivity of the metal vapor, which suppresses the central arc temperature and increases its resistivity.</p>

This work addresses monitoring vesicle fusions occurring during the exocytosis process, which is the main way of intercellular communication. Certain vesicle behaviors may also indicate certain precancerous conditions in cells. For this purpose we designed a system able to detect two main types of exocytosis: a full fusion and a kiss-and-run fusion, based on data from multiple amperometric sensors at once. It uses many instances of small perceptron neural networks in a massively parallel manner and runs on Jetson TX2 platform, which uses a GPU for parallel processing. Based on performed benchmarking, approximately 140,000 sensors can be processed in real time within the sensor sampling period equal to 10 ms and an accuracy of 99$$\%$$ % . The work includes an analysis of the system performance with varying neural network sizes, input data sizes, and sampling periods of fusion signals.