Analyzing Software Architectures: A Semantic Model

Ideally, we want to think of the software architecture phase of a product lifecycle as the phase when the non functional attributes

of the product are determined; a disciplined approach to software architecture consists in identifying the non functional attributes that we want to optimize for the product at hand, and architecting the system accordingly, perhaps at the expense of other desirable but less important attributes. Yet, most current architectural description languages offer no means to represent non functional attributes of architectural components, and (to the best of our language) none offer any means to (automatically) reason about them. In this talk, we discuss our work in defining an architectural description language as an extension of ACME, and in designing a compiler for this language that enables us to compute system-wide attributes from component-level attributes. The talk concludes with a demo of the tool on a sample software architecture.

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Selbstorganisierende Synchronisation

Abstract: Communication and computer networks interconnect an increasing number and diversity of entities, such as mobile devices, sensors, wearable computers, and embedded systems. This trend poses new challenges to the design and operation of networking algorithms and protocols. In particular, the increased system dynamics requires adaptability, distributed operation, and autoconfiguration. One approach to these challenges is to increase the level of self-organization in networks, i.e. to accomplish an intended overall system behavior from local interactions between the individual entities.

In this talk, I focus on a specific aspect of self-organization in networks, namely on self-organized synchronization, as required for medium access, scheduling of sleep phases, and collaborative sensing, to give some examples. We illustrate some synchronization phenomena occurring in nature, explain the theory of pulse-coupled oscillators, and finally present a synchronization solution that has been developed for wireless networks.

Keywords: Selbstorganisation, Synchronisation, Gekoppelte Oszillatoren, Dynamische Systeme, Vernetzte Systeme

CV: Christian Bettstetter is professor and head of the Networked and Embedded Systems institute at the University of Klagenfurt. His main research and teaching interests are in mobile wireless networking, network theory, self-organization, and mobile robots. He is also scientific director and founder of Lakeside Labs GmbH, a research and innovation cluster on self-organizing networked systems.

He studied electrical engineering and information technology at the Technische Universität München (TUM), receiving the Dipl.-Ing. degree in 1998. After a research stay at the University of Notre Dame, Christian joined the institute of communication networks at TUM, where he was a research and teaching staff member until 2003. His doctoral thesis on mobility modeling, connectivity, and adaptive clustering in wireless ad hoc networks was awarded the Dr.-Ing (summa cum laude) degree in 2004. Before becoming a professor, Christian was a senior researcher at DoCoMo Euro-Labs for two years, doing research on medium access and topology aspects of ad hoc networks.

Christian and his team work on the design, modeling, and analysis of future networked communication systems, with a focus on mobile and wireless networking. Major expertise is on algorithms and protocols, stochastic modeling aspects, network theory, and architectures. Current projects address cooperative relaying, self-organized synchronization, and collaborative microdrones. Christian’s teaching portfolio includes various graduate courses on mobile networks and an undergraduate course on electromagnetism.

The publication record includes over 20 articles in journals, magazines, and books, and about 70 papers in refereed conference proceedings. Two of his publications received best paper awards at the IEEE Vehicular Technology Conference, and another one the 2004 outstanding paper award from the German Informationstechnische Gesellschaft (ITG). He also co-authored the Wiley textbook ‚GSM – Architecture, protocols and services.‘ His current h-index, being a measure for the visibility and impact of publications, is 29.

He currently serves as editor for ACM Mobile Computing and Communications Review, committee member of several IEEE and ACM conferences, and project reviewer for the European Commission.

 

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Interaction in “off-screen space”: design possibilities and challenges

Abstract: Many workspaces extend beyond the user’s available viewport, particularly on mobile devices with small screens. Scrolling, panning and zooming are commonly used interaction techniques to manipulate the content of the viewport, but hardware innovations are enabling new forms of interaction. In particular, range sensors and similar technology have recently been added to devices to support interaction in the surrounding “off-screen” space. This talk will sketch possible applications and usage scenarios for off-screen interaction, discuss the human factors involved when interaction is moved into off-screen space, and present the design possibilities and challenges currently investigated by the Interactive Systems research group.

Zur Person: Dr. David Ahlström is a Computer Scientist with interests in developing interactive techniques and interfaces. His current research is focused on modeling and empirically measuring human performance with interactive systems with the aim to understand human factors in computer use. Ahlström received his M.Sc. degree in Computer and Systems Sciences from Stockholm University, Sweden, and his Ph.D. in Computer Science from Klagenfurt University. After that he received an eighteen-months Erwin-Schrödinger-scholarship from The Austrian Science Fund and joined the Computer Science and Software Engineering department at the University of Canterbury in Christchurch, New Zealand. Since 2010 he is back in Klagenfurt and works as an assistant professor in the Interactive Systems Group at the Department of Informatics Systems.

 

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Pulp: An adaptive gossip-based dissemination protocol for multi-source message streams

Gossip-based protocols provide a simple, scalable, and robust way to disseminate messages in large-scale systems. In such protocols, messages are spread in an epidemic manner. Gossiping may take place between nodes using push, pull, or a combination. Push-based systems achieve reasonable latency and high resilience to failures but may impose an unnecessarily large redundancy and overhead on the system. At the other extreme, pull-based protocols impose a lower overhead on the network at the price of increased latencies. A few hybrid approaches have been proposed – typically pushing control messages and pulling data – to avoid the redundancy of high-volume content and single-source streams. Yet, to the best of our knowledge, no other system intermingles push and pull in a multiple-senders scenario, in such a way that data messages of one help in carrying control messages of the other and in adaptively adjusting its rate of operation, further reducing overall cost and improving both on delays and robustness. In this paper, we propose an efficient generic push-pull dissemination protocol, Pulp, which combines the best of both worlds. Pulp exploits the efficiency of push approaches, while limiting redundant messages and therefore imposing a low overhead, as pull protocols do. Pulp leverages the dissemination of multiple messages from diverse sources: by exploiting the push phase of messages to transmit information about other disseminations, Pulp enables an efficient pulling of other messages, which themselves help in turn with the dissemination of pending messages. We deployed Pulp on a cluster and on PlanetLab. Our results demonstrate that Pulp achieves an appealing trade-off between coverage, message redundancy, and propagation delay.

CV: Pascal Felber received his M.Sc. and Ph.D. degrees in Computer Science from the Swiss Federal Institute of Technology. From 1998 to 2002, he has worked at Oracle Corporation and Bell-Labs (Lucent Technologies) in the USA. From 2002 to 2004, he has been an Assistant Professor at Institut EURECOM in France. Since October 2004, he is a Professor of Computer Science at the University of Neuchâtel, Switzerland, working in the field of dependable and distributed systems. He has published over 80 research papers in various journals and conferences.

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Intelligente Energiesysteme

Das Energiesystem erfährt zur Zeit eine stetige Steigerung seiner Komplexität. Es sind vor allem neue Technologien, stochastische Energiequellen, die Informationstechnik und neu entstehende Märkte, die dazu entscheidend beitragen. Komplexität tritt letztendlich ein, wenn ein System aus Subsystemen besteht, die diesen Namen auch verdienen: sie beinhalten Regelkreise, interne Zustände, autonome Aktoren.
Eine Reihe an Forschungsprojekten und Demonstrationsprojekten widmen sich dieser Thematik. Dieser Vortrag wird sich einigen dieser Projekte widmen und vor allem aber auf ein Problem hinweisen: Es fehlt an stimmigen Methoden und Werkzeugen, um solche Systeme designmäßig und während des Betriebs wirklich in den Griff zu bekommen, d.h. zu optimieren und deren Grenzen zu erkennen.
Während es ausgereifte Methoden und Werkzeuge für Teilbereiche – etwa elektrische Maschinen oder Netze – gibt, ist die Beschreibung und Behandlung hybrider Systeme nicht zufriedenstellend gelöst. Die Kombination kontinuierlicher, stochastischer, diskreter und rollen-basierter Prozesse im Smart Grid ist schwer beschreibbar und numerisch fordernd.
Der Vortrag wird erste Erfahrungen auf diesem Gebiet sowie einen Ausblick auf die zukünftigen Forschungsfragen vermitteln.

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Social Software- and Knowledge Engineering

Abstrakt: Mit der ubiquitären Präsenz des World Wide Web und neuer web-basierter, kollaborativer Softwareanwendungen ergeben sich für das Software Engineering zumindest zwei neuartige, theoretisch bedeutsame Heraus-forderungen mit praktischen Implikationen:

(1) Zum einen entstanden durch diese Entwicklung neue Formen von Software, deren Eigenschaften und Gestaltung sich von traditioneller Software deutlich unterscheiden. Sogenannte soziale Software unterscheidet sich zum Beispiel von anderen Arten an Software (wie z.B. Software für Autos oder die Flughafensicherung) durch (i) den sozialen Zweck (ii) die Verwendung auf freiwilliger Basis und (iii) die beispiellose Integration von sozialen Daten über Benutzerverhalten, -ziele und -motivationen in die Struktur und Benutzerschnittstellen der Software. In sozialer Software wird die Interaktion zwischen einzelnen Benutzern und dem System typischerweise durch die Aggregation von Daten einer grossen Menge anderer Benutzer vermittelt und gestaltet. Ein Beispiel derartiger sozialer Softwareeigenschaften findet sich in der tag-basierten Navigation. In sozialer Software können somit traditionell kontrollierbare, nicht-funktionale Softwareeigenschaften (wie zum Beispiel die Navigierbarkeit) dynamisch, d.h. durch das soziale Verhalten ihrer Benutzer, beeinflusst werden. Dies stellt die Entwickler derartiger Software vor grosse Probleme und existierende Softwareentwicklungsmethoden und –verfahren vor neue Herausforderungen.

(2) Zum anderen bewirkt die Verfügbarkeit von sozialer Software, dass sich Softwareentwicklung heute in der Praxis zunehmend als eine verteilte und soziale Aktivität darstellt, bei der Benutzer, Softwareentwickler, Tester und andere Anspruchsgruppen gemeinsam Anforderungen abstimmen, Konflikte lösen, Software entwerfen und Code warten. Unser derzeitiges Verständnis über effektive Methoden und Werkzeuge zur Unterstützung derartiger sozialer Aspekte der Softwareentwicklung ist ungenügend, und eine tiefergehende Auseinandersetzung mit den sozialen Prozessen und Strukturen ist eine unabdingbare Voraussetzung für die Weiterentwicklung von Theorie und Praxis des Software Engineering.

Der Vortrag beleuchtet vergangene und aktuelle Arbeiten meiner Forschungsgruppe im Kontext dieser zwei Herausforderungen, und skizziert einen Forschungsplan für zukünftige Arbeiten.

 

 

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Rückblick: FASTEST: Test Case Generation from Z Specifications [Video, Slides]

Der Rückblick zum TEWI-Kolloquium von Prof. Maximiliano Cristiá, Universidad Nacional de Rosario (Argentina) am 30.03.2012 beinhaltet die Videoaufzeichnung sowie die Folien:

Video

[iframe height=“350″ src=“http://video.aau.at/video.php?video=ftf_cristia.mp4″]

Slides

Abstract

Fastest is a tool that assist software engineers in generating test cases from Z specifications. It provides tool support for a method of model-based testing know as the Test Template Framework. The tool reads a Z specification written in LaTeX markup and waits for commands from the user. Users can apply testing tactics to partition the input space of Z operations thus creating testing trees. Later they can prune these trees to eliminate unsatisfiable test specifications. In a third step, a satisfiability algorithm can be run to find a test case for each leaf in a testing tree. Finally, it is possible to refine these test cases into programs to test the implementation of the Z specification. In this talk I will show how Fastest works on some toy examples and our current research efforts.

Bio:

Maximiliano Cristiá is professor of Software Engineering at Universidad Nacional de Rosario (Argentina) and head of the Software Engineering Group at CIFASIS (International Franco-Argentine Center for Information Sciences and Systems). His research interests include formal methods, particularly model-based testing, software architecture and tool development for the Software Engineer.

 

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A Conceptual-Modeling Approach to Data Extraction

Abstract: For more than a decade we have been studying ways that conceptual modeling can improve our ability to extract semantic data from unstructured and semi-structured information sources such as web pages and historical documents. We start with a data-extraction ontology that comprises a conceptual model together with data frames describing concepts of interest that may be found in an information source. Data-extraction ontologies provide significant advantages over traditional extraction techniques because they give relatively high precision and recall and are robust to changes in the information source structure. However, these benefits come at a price: extraction ontologies require significant expertise to construct, and they apply to a relatively narrow domain of interest. In this lecture I will review our past contributions with a special emphasis on the research techniques we have applied, and I will also describe current areas of research and directions for future experimentation.

CV: Dr. Stephen W. Liddle is academic director of the Kevin and Debra Rollins Center for Entrepreneurship and Technology at Brigham Young University and professor of Information Systems at the Marriott School of Management. Dr. Liddle teaches mobile app development and information systems analysis. Liddle has been a member of BYU’s business school faculty since 1995, after receiving his PhD in Computer Science from BYU. He has been active in the conceptual modeling community for two decades, and currently serves as treasurer of the steering committee for the ER Conference. Liddle’s research interests include conceptual modeling, software engineering environments and tools, data extraction, and e-business. He is particularly interested in mobile application development and applications of conceptual modeling, such as the use of ontologies in data extraction. His work has appeared in journals such as Data and Knowledge Engineering and the Annals of Operations Research, and in respected conferences such as the ER Conference and CIKM, among others. Besides authoring or co-authoring more than 50 refereed academic papers, Liddle is editor of numerous conference and workshop proceedings, and is co-author of the book E-Business: Principles and Strategies for Accountants. Liddle is a member of several advisory boards for tech startups in Utah, and has considerable experience in software development.

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Model-based Systems with Applications in Energy Informatics

Model-based reasoning focuses on formal theories and algorithmic techniques for system-wide diagnosis, planning, and optimization of technical systems.  Distinctive features include the use of compositional models to capture the behavior of components and their interaction, and a generic set of reasoning algorithms.  This talk highlights some of our research in the area of model-based systems, particularly to expand towards on-line estimation and control and hybrids of constraint-based and probabilistic models to capture software behavior and continuous dynamics, and presents some recent applications in the domain of energy informatics and sustainable mobility.

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Self-Organizing Smart Microgrids

Transforming our energy system from hierarchically structured, fossil fuel resources to a distributed, smart sustainable system is one of the great challenges of our time. In this context researchers target their efforts towards modeling of distribution networks, identifying appropriate communication systems, handling configuration complexity, and algorithms for distributed smart micro-grid networks. The first part of the talk depicts how self-organizing configuration and communication mechanisms can contribute to this goal. The second part of the talk gives an introduction to the smart microgid lab, which provides an experimental environment where motivated students can learn and gain practical experience in the domain of smart grids. Finally, I will give an outlook to projects and collaborations in the smart grid area.

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