An integrated approach to testing complex systems

Die steigende Komplexität heutiger Testszenarien für komplexe Systeme erfordert einen ganzheitlichen und offenen Ansatz zur Verwaltung des gesamten Testprozesses. Eine Anwendung klassischer modellbasierter Testansätze, in denen eine präzise und vollständige formale Spezifikation des Systems als Referenz zur automatischen Testfallgenerierung dient, ist in der Praxis nicht möglich.Gründe dafür liegen zum einen im Fehlen einer adäquaten formalen Spezifikation. Komplexe Systeme sind aus verschiedenen Komponenten zusammengesetzt, teils Hardware teils Software und oft auch aus Fremdkomponenten. Dadurch ist es inhärent unrealistisch anzunehmen, dass eine solche formale Spezifikation a priori existiert. Andererseits muss eine ausgereifte Testumgebung die Ausführung von verteilten Testfällen unterstützen, denn die Test-Stimuli und -Beobachtungen können an verschiedenen Teilkomponenten des Systems stattfinden.Diese Arbeit präsentiert einen neuartigen Ansatz für das ganzheitliche Testen komplexer Systeme. Der Ansatz stellt eine 'grobgranulare' Testumgebung zur Verfügung, die mittels einer komponentenbasierten Testfallbeschreibung realisiert ist. Die Basis dafür bildet eine Bibliothek von elementaren, aber intuitiv verständlichen Testfallfragmenten. Die Beziehungen zwischen den Testfallfragmenten sind orthogonal. Dies ermöglicht eine Testbeschreibung und -ausführung, die durch formale Verifikationsmethoden ergänzt wird. Hierdurch können die Testfallbeschreibungsaspekte von Experten des Systems und der verwendeten Testwerkzeuge zu Experten der Systemlogik verschoben werden. Der Ansatz wird durch verschiedene, industrielle Fallstudien in zwei verschiedenen Bereichen illustriert: Computer Telephony Integrations Lösungen und Webbasierte Applikationen. Als Erweiterung des ganzheitlichen Testansatzes wird ein Algorithmus zur a posteriori Generierung approximativer Modelle für komplexe Systeme vorgestellt. Dafür wurde ein bekannter Algorithmus aus dem Maschinellen Lernen an applikationsbedingte Charakteristika angepasst, wie Präfix-Abgeschlossenheit,Input-Determinismus, sowie Unabhängigkeit und Symmetrien zwischen Aktionen. Die resultierenden Modelle können zwar nie exakt sein, in dem Sinne, dass sie das vollständige und korrekte Systemverhalten abbilden. Dennoch können sie von hohem praktischen Nutzen sein, da sie das gesammelte Wissen über das System in einer konsistenten Beschreibungsform repräsentieren.The increasing complexity of today's testing scenarios for complex systems demands an integrated, open, and flexible approach to support the managementof the overall test process. ``Classical'' model-based testing approaches, where a complete and precise formal specification serves as a reference for automatic test generation, are often impractical. Reasons are, on the one hand, the absence of a suitable formal specification. As complex systems are composed of several components, either hardware or software, often pre-built and third party, it is unrealistic to assume that a formal specification exists a priori. On the other hand, a sophisticated test execution environment is needed that can handle distributed test cases. This is because the test actions and observations can take place on different subsystems of the overall system. This thesis presents a novel approach to the integrated testing of complex systems. Our approach offers a coarse grained test environment, realized in terms of a component-based test design on top of a library of elementary but intuitively understandable test case fragments. The relations between the fragments are treated orthogonally, delivering a test design and execution environment enhanced by means of light-weight formal verification methods. In this way we are able to shift the test design issues from total experts of the system and the used test tools to experts of the system's logic only. We illustrate the practical usability of our approach by means of industrial case studies in two different application domains: Computer Telephony Integrated solutions and Web-based applications. As an enhancement of our integrated test approach we provide an algorithm for generating approximate models for complex systems a posteriori. This is done by optimizing a standard machine learning algorithm according to domain-specific structural properties, i.e. properties like prefix-closeness, input-determinism, as well as independency and symmetries of events. The resulting models can never be exact, i.e. reflect the complete and correct behaviour of the considered system. Nevertheless they can be useful in practice, to represent the cumulative knowledge of the system in a consistent description

An algorithm for the proportional division of indivisible items

An allocation of indivisible items among n ≥ 2 players is proportional if and only if each player receives a proportional subset—one that it thinks is worth at least 1/n of the total value of all the items. We show that a proportional allocation exists if and only if there is an allocation in which each player receives one of its minimal bundles, from which the subtraction of any item would make the bundle worth less than 1/n. We give a practicable algorithm, based on players’ rankings of minimal bundles, that finds a proportional allocation if one exists; if not, it gives as many players as possible minimal bundles. The resulting allocation is maximin, but it may be neither envy-free nor Pareto-optimal. However, there always exists a Pareto-optimal maximin allocation which, when n = 2, is also envy-free. We compare our algorithm with two other 2-person algorithms, and we discuss its applicability to real-world disputes among two or more players

Learning nominal automata

We present an Angluin-style algorithm to learn nominal automata, which are acceptors of languages over infinite (structured) alphabets. The abstract approach we take allows us to seamlessly extend known variations of the algorithm to this new setting. In particular we can learn a subclass of nominal non-deterministic automata. An implementation using a recently developed Haskell library for nominal computation is provided for preliminary experiments

An adaptive point sampler on a regular lattice

We present a framework to distribute point samples with controlled spectral properties using a regular lattice of tiles with a single sample per tile. We employ a word-based identification scheme to identify individual tiles in the lattice. Our scheme is recursive, permitting tiles to be subdivided into smaller tiles that use the same set of IDs. The corresponding framework offers a very simple setup for optimization towards different spectral properties. Small lookup tables are sufficient to store all the information needed to produce different point sets. For blue noise with varying densities, we employ the bit-reversal principle to recursively traverse sub-tiles. Our framework is also capable of delivering multi-class blue noise samples. It is well-suited for different sampling scenarios in rendering, including area-light sampling (uniform and adaptive), and importance sampling. Other applications include stippling and distributing objects.publishe

Windy Trees : Computing Stress Response for Developmental Tree Models

We present a novel method for combining developmental tree models with turbulent wind fields. The tree geometry is created from internal growth functions of the developmental model and its response to external stress is induced by a physically-plausible wind field that is simulated by Smoothed Particle Hydrodynamics (SPH).Our tree models are dynamically evolving complex systems that (1) react in real-time to high-frequent changes of the wind simulation; and (2) adapt to long-term wind stress. We extend this process by wind-related effects such as branch breaking as well as budabrasion and drying. In our interactive system the user can adjust the parameters of the growth model, modify wind properties and resulting forces, and define the tree’s long-term response to wind. By using graphics hardware, our implementation runs at interactive rates for moderately large scenes composed of up to 20 tree models

Understanding human perception of building categories in virtual 3D cities : a user study

Virtual 3D cities are becoming increasingly important as a means of visually communicating diverse urban-related information. To get a deeper understanding of a human’s cognitive experience of virtual 3D cities, this paper presents a user study on the human ability to perceive building categories (e.g. residential home, office building, building with shops etc.) from geometric 3D building representations. The study reveals various dependencies between geometric properties of the 3D representations and the perceptibility of the building categories. Knowledge about which geometries are relevant, helpful or obstructive for perceiving a specific building category is derived. The importance and usability of such knowledge is demonstrated based on a perception-guided 3D building abstraction process.publishe

Procedural Urban Forestry

The placement of vegetation plays a central role in the realism of virtual scenes. We introduce procedural placement models (PPMs) for vegetation in urban layouts. PPMs are environmentally sensitive to city geometry and allow identifying plausible plant positions based on structural and functional zones in an urban layout. PPMs can either be directly used by defining their parameters or learned from satellite images and land register data. This allows us to populate urban landscapes with complex 3D vegetation and enhance existing approaches for generating urban landscapes. Our framework’s effectiveness is shown through examples of large-scale city scenes and close-ups of individually grown tree models. We validate the results generated with our framework with a perceptual user study and its usability based on urban scene design sessions with expert users.publishe