Quantitative Timed Analysis of Interactive Markov Chains

Abstract This paper presents new algorithms and accompanying tool support for analyzing interactive Markov chains (IMCs), a stochastic timed 1 1 2-player game in which delays are exponentially distributed. IMCs are compositional and act as semantic model for engineering for-malisms such as AADL and dynamic fault trees. We provide algorithms for determining the extremal expected time of reaching a set of states, and the long-run average of time spent in a set of states. The prototypical tool Imca supports these algorithms as well as the synthesis of ε-optimal piecewise constant timed policies for timed reachability objectives. Two case studies show the feasibility and scalability of the algorithms.

Probabilistic Model-Based Safety Analysis

Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional approaches is that the analysis of the whole system gives more precise results. Only few model-based approaches have been applied to answer quantitative questions in safety analysis, often limited to analysis of specific failure propagation models, limited types of failure modes or without system dynamics and behavior, as direct quantitative analysis is uses large amounts of computing resources. New achievements in the domain of (probabilistic) model-checking now allow for overcoming this problem. This paper shows how functional models based on synchronous parallel semantics, which can be used for system design, implementation and qualitative safety analysis, can be directly re-used for (model-based) quantitative safety analysis. Accurate modeling of different types of probabilistic failure occurrence is shown as well as accurate interpretation of the results of the analysis. This allows for reliable and expressive assessment of the safety of a system in early design stages

A tutorial on interactive Markov chains

Interactive Markov chains (IMCs) constitute a powerful sto- chastic model that extends both continuous-time Markov chains and labelled transition systems. IMCs enable a wide range of modelling and analysis techniques and serve as a semantic model for many industrial and scientific formalisms, such as AADL, GSPNs and many more. Applications cover various engineering contexts ranging from industrial system-on-chip manufacturing to satellite designs. We present a survey of the state-of-the-art in modelling and analysis of IMCs.\ud We cover a set of techniques that can be utilised for compositional modelling, state space generation and reduction, and model checking. The significance of the presented material and corresponding tools is highlighted through multiple case studies

From probabilistic counterexamples via causality to fault trees

Abstract. In recent years, several approaches to generate probabilistic counterexamples have been proposed. The interpretation of stochastic counterexamples, however, continues to be problematic since they have to be represented as sets of paths, and the number of paths in this set may be very large. Fault trees (FTs) are a well-established industrial technique to represent causalities for possible system hazards resulting from system or system component failures. In this paper we suggest a method to automatically derive FTs from counterexamples, including a mapping of the probability information onto the FT. We extend the structural equation approach by Pearl and Halpern, which is based on Lewis counterfactuals, so that it serves as a justification for the causality that our proposed FT derivation rules imply. We demonstrate the usefulness of our approach by applying it to an industrial case study.

Rationelle Energieverwendung: Ein Literaturüberblick des Jahres 1997

Trotz eines Anstiegs des Bruttoinlandsproduktes um rund 2,2 % im Jahre 1997 nahm der Primärenergieverbrauch in Deutschland von 503,9 Mio t SKE auf 494,4 Mio t SKE ab. Dieser Rückgang ist fast völlig auf das wärmere Wetter dieses Jahres zurückzuführen. Temperatur bereinigt hat sich die Primärenergieintensität nur um 0,5 % reduziert, das heißt, der Einfluß der rationellen Energieverwendung hat sich im Vergleich zu den Jahren seit 1990 noch weiter abgeschwächt. Trotzdem werden von vielen Technologen langfristig die Energieeinsparpotentiale in vielen Sektoren für sehr groß gehalten, so daß diese Potentiale auch 1998 eine bleibende Herausforderung für die Wirtschaft, die Effizienzproduzenten und die Politik sein werden. Der intersektorale Strukturwandel zugunsten weniger energieintensiver Sektoren innerhalb der deutschen Volkswirtschaft hat sich auch 1997 fortgesetzt. Dabei wird die Intensität der Wandlungsprozesse in Ostdeutschland noch immer doppelt so hoch eingeschätzt wie in Westdeutschland. Aus detaillierten Untersuchungen geht hervor, daß der Strukturwandel innerhalb des Industriesektors nur in Ostdeutschland einen Beitrag zur Minderung des Energieverbrauchs und der CO2-Emissionen leistete. Der Autor führt eine Reihe von Maßnahmen an, die in der Industrie eine rationelle Energieverwendung förderten (neue Verfahren und Anlagen mit verbesserten Ausbeuten, geringeren Abmessungen und reduziertem Energieverbrauch; energieeffizientere Reaktionsführungen; Einsatz neuer Katalysatoren; Anlagen- und Verfahrensoptimierungen; Einbeziehung von Simulationen in die Steuerung von Prozessen; verstärkter Einsatz von Fuzzy-Verfahren und neuronalen Netzen und anderes). Mit der Festlegung von Emissionsminderungspflichten für Industrieländer im Klimaprotokoll von Kyoto dürfte sich der Schwerpunkt der Umweltpolitik auf die Fragen verschieben, die noch nicht geregelt sind. Hierzu zählen die Details zum internationalen Handel mit Emissionsrechten und die Anrechnung gemeinsam umgesetzter Klimaschutzprojekte (zwei Instrumente, die die Entwicklung der Energieeffizienz weltweit beschleunigen könnten) sowie die Anrechnung von CO2-Senken

On the Synergy of Probabilistic Causality Computation and Causality Checking

Abstract. In recent work on the safety analysis of systems we have shown how causal relationships amongst events can be algorithmically inferred from probabilistic counterexamples and subsequently be mapped to fault trees. The resulting fault trees were significantly smaller and hence easier to understand than the corresponding probabilistic counterexample, but still contain all information needed to discern the causes for the occurrence of a hazard. More recently we have developed an approach called Causality Checking which is integrated into the state-space exploration algorithms used for qualitative model checking and which is capable of computing causality relationships on-the-fly. The causality checking approach outperforms the probabilistic causality computation in terms of run-time and memory consumption, but can not provide a probabilistic measure. In this paper we combine the strengths of both approaches and propose an approach where the causal events are computed using causality checking and the probability computation can be limited to the causal events. We demonstrate the increase in performance of our approach using several case studies.

Efficient Anytime Techniques for Model-Based Safety Analysis

Safety analysis investigates system behavior under faulty conditions. It is a fundamental step in the design of complex systems, that is often mandated by certification procedures. Safety analysis includes two key steps: the construction of all minimal cut sets (MCSs) for a given property (i.e. the sets of basic faults that may cause a failure), and the computation of the corresponding probability (given probabilities for the basic faults). Model-based Safety Analysis relies on formal verification to carry out these tasks. However, the available techniques suffer from scalability problems, and are unable to provide useful results if the computation does not complete. In this paper, we investigate and evaluate a family of IC3-based algorithms for MCSs computation. We work under the monotonicity assumption of safety analysis (i.e. an additional fault can not prevent the violation of the property). We specialize IC3-based routines for parameter synthesis by optimizing the counterexample generalization, by ordering the exploration of MCSs based on increasing cardinality, and by exploiting the inductive invariants built by IC3 to accelerate convergence. Other enhancements yield an “anytime” algorithm, able to produce an increasingly precise probability estimate as the discovery of MCSs proceeds, even when the computation does not terminate. A thorough experimental evaluation clearly demonstrates the substantial advances resulting from the proposed methods

Evaluación de hemerotecas de prensa digital: indicadores y ejemplos de buenas prácticas

La gran mayoría de los diarios digitales facilitan el acceso a la información retrospectiva mediante servicios de hemerotecas o archivos de prensa, un producto de notable interés para bibliotecas y otros servicios de información. El objetivo de este estudio es determinar cuáles son los indicadores fundamentales para la evaluación de hemerotecas digitales y, además, señalar ejemplos de buenas prácticas en España para cada uno de ellos. Se propone una relación de veintisiete indicadores agrupados en cuatro grandes apartados (aspectos generales, contenidos, sistema de consulta, y presentación de resultados), se describe cada uno de ellos y se incluye algún ejemplo de buena aplicación. Metodológicamente, se ha partido de la revisión de la bibliografía especializada en evaluación de recursos web, bases de datos y hemerotecas digitales, así como del análisis de hemerotecas de diarios de España y Catalunya. La utilización de estos indicadores puede ser de utilidad para que bibliotecas y otros servicios de información puedan orientar a sus usuarios en la consulta retrospectiva de información de prensa