A formal approach to autonomic systems programming: the SCEL Language

The autonomic computing paradigm has been proposed to cope with size, complexity and dynamism of contemporary software-intensive systems. The challenge for language designers is to devise appropriate abstractions and linguistic primitives to deal with the large dimension of systems, and with their need to adapt to the changes of the working environment and to the evolving requirements. We propose a set of programming abstractions that permit to represent behaviors, knowledge and aggregations according to specific policies, and to support programming context-awareness, self-awareness and adaptation. Based on these abstractions, we define SCEL (Software Component Ensemble Language), a kernel language whose solid semantic foundations lay also the basis for formal reasoning on autonomic systems behavior. To show expressiveness and effectiveness of SCEL’s design, we present a Java implementation of the proposed abstractions and show how it can be exploited for programming a robotics scenario that is used as a running example for describing features and potentials of our approac

A new type of reconstruction on the InSb() surface determined by grazing incidence X-ray diffraction

The (3×3) reconstruction of the InSb( ) surface has been investigated by grazing incidence X-ray diffraction and scanning tunneling microscopy. The structure is characterized by 6-atom rings on top of a slightly buckled InSb top double layer. Two types of rings have been found, an elliptic ring consisting of 4 In and 2 Sb atoms and a trigonal ring with 3 In and 3 Sb atoms. The bond angles and lengths are consistent with the concept of rehybridization and depolarization which explains the reconstructions of the (111) and (110) surfaces

An Analysis Pathway for the Quantitative Evaluation of Public Transport Systems

We consider the problem of evaluating quantitative service-level agreements in public services such as transportation systems. We describe the integration of quantitative analysis tools for data fitting, model generation, simulation, and statistical model-checking, creating an analysis pathway leading from system measurement data to verification results. We apply our pathway to the problem of determining whether public bus systems are delivering an appropriate quality of service as required by regulators. We exercise the pathway on service data obtained from Lothian Buses about the arrival and departure times of their buses on key bus routes through the city of Edinburgh. Although we include only that example in the present paper, our methods are sufficiently general to apply to other transport systems and other cities

A new measure of travel time reliability for in-vehicle navigation systems

This article introduces a new measure of travel time reliability for implementation in the dynamic routing algorithm of an intelligent car navigation system. The measure is based on the log-normal distribution of travel time on a link and consists of two indices corresponding to the extreme values of the distribution, such that they reflect the shortest and longest travel times that may be experienced on the link. Through a series of mathematical manipulations, the indices are expressed in terms of the characteristic values of the speed distribution on the link. An expression relating the indices of a route and the indices of the individual links forming it is derived. The accuracy of the measure is then assessed through a field experiment and the results are presented

Statistical Model Checking for Product Lines

International audienceWe report on the suitability of statistical model checking forthe analysis of quantitative properties of product line models by an extendedtreatment of earlier work by the authors. The type of analysis thatcan be performed includes the likelihood of specific product behaviour,the expected average cost of products (in terms of the attributes of theproducts’ features) and the probability of features to be (un)installed atruntime. The product lines must be modelled in QFLan, which extendsthe probabilistic feature-oriented language PFLan with novel quantitativeconstraints among features and on behaviour and with advancedfeature installation options. QFLan is a rich process-algebraic specifi-cation language whose operational behaviour interacts with a store ofconstraints, neatly separating product configuration from product behaviour.The resulting probabilistic configurations and probabilistic behaviourconverge in a discrete-time Markov chain semantics, enablingthe analysis of quantitative properties. Technically, a Maude implementationof QFLan, integrated with Microsoft’s SMT constraint solver Z3,is combined with the distributed statistical model checker MultiVeStA,developed by one of the authors. We illustrate the feasibility of our frameworkby applying it to a case study of a product line of bikes

Optimization of global production scheduling with deep reinforcement learning

Industrie 4.0 introduces decentralized, self-organizing and self-learning systems for production control. At the same time, new machine learning algorithms are getting increasingly powerful and solve real world problems. We apply Google DeepMind's Deep Q Network (DQN) agent algorithm for Reinforcement Learning (RL) to production scheduling to achieve the Industrie 4.0 vision for production control. In an RL environment cooperative DQN agents, which utilize deep neural networks, are trained with user-defined objectives to optimize scheduling. We validate our system with a small factory simulation, which is modeling an abstracted frontend-of-line semiconductor production facility

A formal approach to autonomic systems programming: the SCEL language

Software-intensive cyber-physical systems have to deal with massive numbers of components, featuring complex interactions among components and with humans and other systems. Often, they are designed to operate in open and non-deterministic environments, and to dynamically adapt to new requirements, technologies and external conditions. This class of systems has been named ensembles and new engineering techniques are needed to address the challenges of developing, integrating, and deploying them. In the paper, we briefly introduce SCEL (Software Component Ensemble Language), a kernel language that takes a holistic approach to programming autonomic computing systems and aims at providing programmers with a complete set of linguistic abstractions for programming the behavior of autonomic components and the formation of autonomic components ensembles, and for controlling the interaction among different components

Programming and Verifying Component Ensembles

A simplified version of the kernel language SCEL, that we call SCELlight, is introduced as a formalism for programming and verifying properties of so-called cyber-physical systems consisting of software-intensive ensembles of components, featuring complex intercommunications and interactions with humans and other systems. In order to validate the amenability of the language for verification purposes, we provide a translation of SCELlight specifications into Promela. We test the feasibility of the approach by formally specifying an application scenario, consisting of a collection of components offering a variety of services meeting different quality levels, and by using SPIN to verify that some desired behaviors are guaranteed