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[Context and motivation] Communication in distributed software development is usually supported by issue tracking systems. Within these systems, most of the communication is stored as unstructured natural language text. The natural language text, however, contains much information with respect to requirements management, e.g. discussion, clarification and prioritization of features, bugs, and refactorings. [Question] This paper investigates the information stored in the issue tracking systems of four different open-source projects. It categorizes the text and reports on the distribution of issue types and information types. [Principal ideas/results] A manual analysis of 80 issues, using a grounded approach, is conducted to derive a taxonomy of issue types and information types. Subsequently, the taxonomy is used as a codebook, to manually categorize and structure the text in another 120 issues. [Contribution] The first contribution of this paper is the taxonomy of issue and information types and the second contribution is an in-depth analysis of the natural language data and the communication. This analysis showed, for example, that information with respect to prioritization and scheduling can be found in natural language data, whether the ITS supports such tasks in a structured way or not.
Comparison of the subject-oriented and the Petri net based approach for business process automation
(2015)
The subject-oriented modelling approach [5] significally differs from the classic Petri net based approach of many business process modeling languages like EPC [9], Business Process Model and Notation (BPMN) [11], and also Yet Another Workflow Language (YAWL) [10]. In this work, we compare the two approaches by modeling a case study called "Procure to Pay"[3], a typical business process where some equipment for a construction site is rented and finally paid. The case study is not only modelled but also automated using the Metasonic Suite for the subject-oriented and YAWL for the Petri net based approach.
This book presents bond graph model-based fault detection with a focus on hybrid system models. The book addresses model design, simulation, control and model-based fault diagnosis of multidisciplinary engineering systems. The text beings with a brief survey of the state-of-the-art, then focuses on hybrid systems. The author then uses different bond graph approaches throughout the text and provides case studies.
Perception is one of the most important cognitive capabilities of an entity since it determines how an entity perceives its environment. The presented work focuses on providing cost efficient but realistic perceptual processes for intelligent virtual agents (IVAs) or NPCs with the goal of providing a sound information basis for the entities' decision making processes. In addition, an agent-central perception process should rovide a common interface for developers to retrieve data from the IVAs' environment. The overall process is evaluated by applying it to a scenario demonstrating its benefits. The evaluation indicates, that such a realistically simulated perception process provides a powerful instrument to enhance the (perceived) realism of an IVA's simulated behavior.
Informatikerinnen und Informatiker aller Fachrichtungen müssen die grundlegenden Konzepte, Methoden und Verfahren, die der Entwicklung und dem Einsatz von Informations- und Kommunikationstechnologien zugrunde liegen, verstehen und bei der Lösung von Problemen anwenden können. Das Buch stellt die algebraischen und zahlentheoretischen Grundlagen dafür vor und wendet diese bei der Lösung praktischer Problemstellungen, wie modulare Arithmetik, Primzahltests und Verschlüsselung an. Das Verständnis der Begriffe und deren Zusammenhänge und Zusammenwirken wird u.a. durch Lernziele, integrierte Übungsaufgaben mit Musterlösungen und Marginalien unterstützt. Das Buch ist zum Selbststudium gut geeignet.
In the field of domestic service robots, recovery from faults is crucial to promote user acceptance. In this context we focus in particular on some specific faults, which arise from the interaction of a robot with its real world environment. Even a well-modelled robot may fail to perform its tasks successfully due to unexpected situations, which occur while interacting. These situations occur as deviations of properties of the objects (manipulated by the robot) from their expected values. Hence, they are experienced by the robot as external faults.
Unexpected Situations in Service Robot Environment: Classification and Reasoning Using Naive Physics
(2014)
Current computer architectures are multi-threaded and make use of multiple CPU cores. Most garbage collections policies for the Java Virtual Machine include a stop-the-world phase, which means that all threads are suspended. A considerable portion of the execution time of Java programs is spent in these stop-the-world garbage collections. To improve this behavior, a thread-local allocation and garbage collection that only affects single threads, has been proposed. Unfortunately, only objects that are not accessible by other threads ("do not escape") are eligible for this kind of allocation. It is therefore necessary to reliably predict the escaping of objects. The work presented in this paper analyzes the escaping of objects based on the line of code (program counter – PC) the object was allocated at. The results show that on average 60-80% of the objects do not escape and can therefore be locally allocated.
Improving data acquisition techniques and rising computational power keep producing more and larger data sets that need to be analyzed. These data sets usually do not fit into a GPU's memory. To interactively visualize such data with direct volume rendering, sophisticated techniques for problem domain decomposition, memory management and rendering have to be used. The volume renderer Volt is used to show how CUDA is efficiently utilised to manage the volume data and a GPU's memory with the aim of low opacity volume renderings of large volumes at interactive frame rates.
In contrast to projection-based systems, large, high resolution multi-display systems offer a high pixel density on a large visualization area. This enables users to step up to the displays and see a small but highly detailed area. If the users move back a few steps they don't perceive details at pixel level but will instead get an overview of the whole visualization. Rendering techniques for design evaluation and review or for visualizing large volume data (e.g. Big Data applications) often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates.
A view direction based (VDB) rendering technique renders the user's central field of view in high quality whereas the surrounding is rendered with a level-of-detail approach depending on the distance to the user's central field of view. This approach mimics the physiology of the human eye and conserves the advantage of highly detailed information when standing close to the multi-display system as well as the general overview of the whole scene. In this paper we propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.