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Den original Samsung WIS12ABGNX/XEC WLAN-Dongle für TV
der kompatibel mit allen TV Geräten der E-Serie ist gibt es für ca. 40 Euro bei Amazon.

Alternativ kursieren im Netz auch Anleitungen mit denen man den günstigeren Edimax EW-7718Un WLAN Stick so “umprogrammieren” kann das er am Samsung TV funktioniert. Da man hier aber eine Menge Arbeit in kauf nehmen muss und nur 15 Euro spart ist meine Empfehlung den original Stick zu kaufen.

Wer es trotzdem mit dem Edimax Stick versuchen möchte findet hier die Anleitungen (auf Englisch):

Anleitung 1, Anleitung 2

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The slides of my talk are available here.

Abstract:
With the increasing growth of the size and complexity of modern safety-critical systems, the demand for model based engineering methods that both help in architecting such systems and to asses their safety and correctness becomes increasingly obvious. Causality checking is an automated method for formal causality analysis of system models and system execution traces. In this paper we report on work in progress towards an on-the-fly approach for causality checking of system models. We also sketch how this approach can be applied in model-based system analysis when assessing the system’s functional correctness.

The post Causality Checking for Complex System Models (Talk at VMCAI 2013) appeared first on Florian Leitner-Fischer.

A video of the lecture is available online here.

Here is the abstract of his talk:

I will introduce Causality Checking, a technique extending model checking designed to establish causalities for safety property violations in system models. Causality Checking is based on counterfactual reasoning. In particular, it is based on an adoption of the Halpern/Pearl Structural Equation Model (SEM) for establishing actual causes. Causality Checking takes advantage of the fact that using a model checker it is fairly easy to compute both “bad” as well as alternate “good” worlds, where a world corresponds to a finite execution sequence.

Based on our adoption of the SEM I will show how causalities can be determined by performing difference computations on the sets of bad and good executions of a model. I will present two approaches how to perform this computation: one based on an explicit enumeration of all bad and good execution traces of a model, and another one based on an on-the-fly algorithm integrated into standard state space search algorithms used in explicit state model checking. I will sketch applications of Causality Checking to systems analysis by considering a number of case studies, including functional and probabilistic models. I will illustrate how the computed causalities can be displayed as fault trees and serve as a basis for system debugging.

The post Causality Checking at Microsoft Research appeared first on Florian Leitner-Fischer.

There a two great benefits:

• You can “follow”  authors and automatically get an email alert whenever they have published a paper, in my opinion a great way to keep track of what is going on in your research field.
• You can “follow” citations of authors and for instance automatically get an email alert when somebody cites your paper.

A minor but still interesting point is that you can create a public or private author profile where

• all your publications are listed,
• metrics like citation count, h-index, i10-index and so on are computed,
• and you can enter a link to your current website.

My public Google Scholar Author Profile can be found here. 

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CausCheck : Causality Checking for Complex System Models

With the increasing complexity of modern safety-critical systems, the need for model based engineering methods that both help in architecting such systems and to asses their safety and correctness becomes increasingly obvious. Due to the size of the systems, traditional techniques like reviews and testing, on the one hand, and manual fault tree analysis or failure mode and effect analysis, on the other hand, can only be applied to limited parts of the system. The main reason for this limitation lies in the vast amount of time and resources that is consumed by manually executing those techniques. In order to be able to asses the correctness and safety of these systems in a comprehensive manner automated or, at least, computer-aided techniques are needed.

Model Checking is an established technique for the automated analysis of system properties. If a model of the system and a formalized property are given to the model checker, it automatically checks whether it can find property violations. In case a safety property is violated, the model checker returns a counterexample, which consists of a system execution trace leading to the property violation. In recent work LeiLeu11, LeiLeu11a we have presented the QuantUM approach which allows for automatic translation of system and software architecture models in UML to the input language of the probabilistic model checker PRISM.

The automatic translation of the UML model to PRISM saves time and resources and prevents errors that where frequently introduced in the manual translation process that was previously used. The remaining challenge is the identification of the causes of the property violation and representing this information in a way that it is interpretable on the level of the UML model. The counterexamples that are computed by the model checker help in retracing the system executions leading to the property violation, but they can only be interpreted at the level of the analysis model. While the visualization of the graph structure of a probabilistic counterexample helps to analyze the counterexamples, it is still difficult to compare the thousands of paths in the counterexample with each other and to discern causal factors during fault analysis.

From Counterexamples via Causality to Fault Trees

In order to lift the probabilistic counterexamples generated by the model checker to the level of the UML model, we propose an automatic approach in KunLL11b that computes causality relationships based on a complete set of probabilistic counterexamples and visualizes the computed causality relationships as fault trees. Fault trees are an industrial standard method to document graphically which combination of events can cause a system hazard. The justification for the causalities determined by our method are based on an adoption of the Structural Equation Model of Halpern and Pearl. We illustrate how to use this model in the analysis of computing systems and extend it to account for event orderings as causal factors. We present an over-approximating implementation of the causality tests derived from the extended model.

We demonstrate that our approach improves and facilitates the analysis of safety critical systems. The resulting fault trees are significantly smaller and hence easier to understand than the probabilistic stochastic counterexample, but still contain all information needed to discern the causes for the occurrence of a hazard.

On-The-Fly Causality Checking

The causality computation for probabilistic counterexamples and the mapping of the causality relationships to fault trees helps to understand how the failure of the systems was caused. Experiments in BeeKLLP12 indicate that the computation of the probabilistic counterexamples, on which the causality computation method relies, accounts for the majority of run-time and memory consumption needed for the causality computation.

The main reason for this is that the probability for each execution trace of the counterexample needs to be computed. While the probability of a system fault is of interest, the information which events cause the system failure is more important to the user. Consequently, we extend QuantUM with a translation from UML models to Promela, the input language of the qualitative model checker SPIN, and adapt our causality method to work on counterexamples that were generated using SPIN. This qualitative method scales much better since no probabilities have to be computed. It is, however, still necessary to enumerate and store all counterexample execution traces and all good execution traces in order to compute the causality relationships. We address this issue in LeiLeu12a and LeiLeu12 by extending the causality model to make it applicable to concurrent system models that are specified by transition systems. Furthermore, we propose a causality checking algorithm which can be integrated into a depth-first search or breadth-first search algorithm that is used for the state space exploration during model checking.

The post CausCheck : Causality Checking for Complex System Models appeared first on Florian Leitner-Fischer.

Ich liebe mein Apple Wireless Keyboard, aber was mich gelegentlich nervt ist, dass die Batterien oder Akkus immer im ungünstigsten Moment leer sind. Deswegen habe ich mir nun bei Amazon die Logitech K750 Mac Tastatur mit Solarzellen angeschafft. Das Spezielle an dieser Tastatur ist, dass sie ähnlich wie die bekannten Solar-Taschenrechner funktioniert, nur dass sie zusätzlich auch einen integrierten Akku besitzt, so dass man auch bei Dunkelheit laut Logitech bis zu 3 Wochen mit der Tastatur arbeiten kann. Ein weiterer Pluspunkt gegenüber dem Apple Wireless Keyboard ist der integrierte Nummernblock.

Meine Eindrücke

Vom Design her ist die Tastatur sehr ähnlich zu den Mac Keyboards und passt somit sehr gut zu iMac, MacBook Air oder MacBook Pro. In Puncto Bedienung und Haptik steht das Logitech Mac Keyboard der Apple Tastatur auch in nichts nach. Alles in allem eine klare Empfehlung zum Kauf!

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English:

Functional Safety
The Safety Critical Systems Handbook

German:

Funktionale Sicherheit
Funktionale Sicherheit in der Praxis

The post Functional Safety Literature / Books (ISO 26262, IEC 61508) appeared first on Florian Leitner-Fischer.

Here’s some ideas, some mine, some are inspired by a similar post of Scott Hanselman:

• Set-aside time, like one or two hours per week, to read technical books or papers related to your field of work.
• Set-aside time to read one technical paper or book that is not related to your field of work per month.
• Listen to podcasts, or watch screencasts about new technologies and approaches.
• Attend conferences and talks and most importantly try to ask questions or at least write down questions and try to figure out the answer for your self.
• Discuss problems with your co-workers, you might be surprised how much you can learn from a good discussion.
• Help others, sometimes there is no better and satisfactory way than helping someone to solve a technical problem.
• Try something new! Whether it is a new programmin language, new software architecting tool or a new software process model you’ll never know when you need it.

The post Sharpen the Saw for Computer Scientists appeared first on Florian Leitner-Fischer.

The QuantUM Approach

When developing a safety-critical system it is essential to obtain an assessment of different design alternatives. In particular, an early safety assessment of the architectural design of a system is desirable. In spite of the plethora of available formal quantitative analysis methods it is still difficult for software and system architects to integrate these techniques into their every day work. This is mainly due to the lack of methods that can be directly applied to architecture level models, for instance given as UML diagrams. Also, it is necessary that the description methods used do not require a profound knowledge of formal methods. Our approach bridges this gap and improves the integration of quantitative safety analysis methods into the development process. All inputs of the analysis are specified at the level of a UML model. This model is then automatically translated into the analysis model, and the results of the analysis are consequently represented on the level of the UML model. Thus the analysis model and the formal methods used during the analysis are hidden from the user.

Our approach depicted in the Figure above can be summarized by identifying the following steps:

• Our UML extension is used to annotate the UML model with all information that is needed to perform a dependability analysis.
• The annotated UML model is then exported in the XML Metadata Interchange (XMI) format which is the standard format for exchanging UML models.
• Subsequently, our QuantUM Tool parses the generated XMI file and generates the analysis model in the input language of the probabilistic model checker PRISM as well the properties to be verified.
• For the analysis we use the probabilistic model checker PRISM together with DiPro in order to compute probabilistic counterexamples representing paths leading to a hazard state.
• The resulting counterexamples can then be transformed into a fault tree that can be interpreted at the level of the UML model. Alternatively, they can be mapped onto a UML sequence diagram which can be displayed in the UML modeling tool containing the original UML model.

Key Features of QuantUM

• QuantUM Profile for UML and SysML
  Extension of the UML and SysML with stereotypes. Specification of safety requirements, dependability characteristics (failure modes, …), failure propagation, component dependencies, safety mechanisms (repair management, redundancy structures) directly in the architectural model with your existing UML / SysML CASE tool.
• Probabilistic Analsysis / pFMEA
  The annotated UML Model is automatically translated into the input language of a probabilistic model checker, which computes the probability of  safety requirements of hazards. In addition a probabilistic FMEA can be performed automatically.
• Automated Fault Tree Generation
  (Quantitative) Fault Trees identifying the events causing the violation of a safety requirement or a hazard are automatically generated the analysis.
• Result Representation in UML / SysML
  System executions violating safety requirements or causing a hazard can be displayed as UML sequence diagrams.

Industrial Usage

The QuantUM approach was applied in several industrial case studies and can be used with all major UML / SysML case tools (e.g. IBM Rational Rhapsody, IBM Rational Software Architect, Sparxsystem Enterprise Architect, …)

More Information

More Information on the theory and methods behind QuantUM can be found on the publications site. As soon as the first prototype is available
it will be announced here! Stay tuned!

The post QuantUM: Safety Analysis of Complex System and Software Architectures appeared first on Florian Leitner-Fischer.