Eine Architektur für Programmsynthese aus natürlicher Sprache

This book presents an architecture for programming in natural language called NLCI. It decouples the application domain from the text analyses: NLCI is an extensible architecture and its components are reusable. NLCI is evaluated with two case studies in two radically different domains: translating commands for a home automation system (openHAB) and generating 3D animations from English scripts with Alice

Computational Complexity in Tile Self-Assembly

One of the most fundamental and well-studied problems in Tile Self-Assembly is the Unique Assembly Verification (UAV) problem. This algorithmic problem asks whether a given tile system uniquely assembles a specific assembly. The complexity of this problem in the 2-Handed Assembly Model (2HAM) at a constant temperature is a long-standing open problem since the model was introduced. Previously, only membership in the class coNP was known and that the problem is in P if the temperature is one (τ = 1). The problem is known to be hard for many generalizations of the model, such as allowing one step into the third dimension or allowing the temperature of the system to be a variable, but the most fundamental version has remained open. In this Thesis I will cover verification problems in different models of self-assembly leading to the proof that the UAV problem in the 2HAM is hard even with a small constant temperature (τ = 2), and finally answer the complexity of this problem (open since 2013). Further, this result proves that UAV in the staged self-assembly model is coNP-complete with a single bin and stage (open since 2007), and that UAV in the q-tile model is also coNP-complete (open since 2004). We reduce from Monotone Planar 3-SAT with Neighboring Variable Pairs, a special case of 3SAT recently proven to be NP-hard

Cooperative Navigation for Mixed Human–Robot Teams Using Haptic Feedback

In this paper, we present a novel cooperative navigation control for human–robot teams. Assuming that a human wants to reach a final location in a large environment with the help of a mobile robot, the robot must steer the human from the initial to the target position. The challenges posed by cooperative human–robot navigation are typically addressed by using haptic feedback via physical interaction. In contrast with that, in this paper, we describe a different approach, in which the human–robot interaction is achieved via wearable vibrotactile armbands. In the proposed work, the subject is free to decide her/his own pace. A warning vibrational signal is generated by the haptic armbands when a large deviation with respect to the desired pose is detected by the robot. The proposed method has been evaluated in a large indoor environment, where 15 blindfolded human subjects were asked to follow the haptic cues provided by the robot. The participants had to reach a target area, while avoiding static and dynamic obstacles. Experimental results revealed that the blindfolded subjects were able to avoid the obstacles and safely reach the target in all of the performed trials. A comparison is provided between the results obtained with blindfolded users and experiments performed with sighted people

A criteria based function for reconstructing low-sampling trajectories as a tool for analytics

Abstract: Mobile applications equipped with Global Positioning Systems have generated a huge quantity of location data with sampling uncertainty that must be handled and analyzed. Those location data can be ordered in time to represent trajectories of moving objects. The data warehouse approach based on spatio-temporal data can help on this task. For this reason, we address the problem of personalized reconstruction of low-sampling trajectories based on criteria over a graph for including criteria of movement as a dimension in a trajectory data warehouse solution to carry out analytical tasks over moving objects and the environment where they moveMaestrí

Zielorientierte Erkennung und Behebung von Qualitätsdefiziten in Software-Systemen am Beispiel der Weiterentwicklungsfähigkeit

The evolvability of software systems is one of the key issues when considering their long term quality. Continuous changes and extensions of these systems are neccessary to adjust them to new or changing requirements. But the changes often cause quality deficiencies, which lead to an increase in complexity or an architectural decay. Especially quality deficiencies within the specification or the architecture of a software system can heavily impair a software system.To counteract this, a method is developed in this work to support the analysis of a quality goal in order to identify the quality deficiencies which hinder the achievement of the quality goal. Both the detection and the removal of quality deficiencies are accomplished in a systematic way. The method integrates detection of these quality deficiencies and their removal by reengineering activities based on rules. The detection of quality deficiencies is performed by means of measurable quality attributes which are derived from a quality goal, such as evolvability. In order to demonstrate the practicability of the method, the quality goal evolvability is taken as an example. This work shows how a software system can be evaluated with regard to evolvability based on structural dependencies and which reengineering activities will improve the system in the direction of this quality goal.To evaluate the method, it was applied within an industrial case study. By analyzing the given software system a large number of different quality deficiencies were detected. Afterwards the system's evolvability was improved substantially by reengineering activities proposed by the method.Für unternehmenskritische Software-Systeme, die langlebig und erweiterbar sein sollen, ist das Qualitätsziel Weiterentwicklungsfähigkeit essentiell. Kontinuierliche Änderungen und Erweiterungen sind unabdingbar, um solche Software-Systeme an neue oder veränderte Anforderungen anzupassen. Diese Maßnahmen verursachen aber auch oft Qualitätsdefizite, die zu einem Anstieg der Komplexität oder einem Verfall der Architektur führen können. Gerade Qualitätsdefizite in der Spezifikation oder Architektur können Software-Systeme stark beeinträchtigen.Um dem entgegenzuwirken, wird in dieser Arbeit eine Methode entwickelt, welche die Einhaltung von Qualitätszielen bewerten kann. Dadurch wird sowohl das Erkennen als auch das Beheben von Qualitätsdefiziten in der Software-Entwicklung ermöglicht. Qualitätsdefizite werden anhand einer am Qualitätsziel orientierten und regelbasierten Analyse erkannt und durch zugeordnete Reengineering-Aktivitäten behoben. Als Beispiel für ein Qualitätsziel wird die Weiterentwicklungsfähigkeit von Software-Systemen betrachtet. Es wird gezeigt, wie dieses Qualitätsziel anhand von strukturellen Abhängigkeiten in Software-Systemen bewertet und durch gezielte Reengineering-Aktivitäten verbessert werden kann.Um die Methode zu validieren, wurde eine industrielle Fallstudie durchgeführt. Durch den Einsatz der Methode konnten eine Vielzahl von Qualitätsdefiziten erkannt und behoben werden. Die Weiterentwicklungsfähigkeit des untersuchten Software-Systems wurde durch die vorgeschlagenen Reengineering-Aktivitäten entscheidend verbessert

A dependency-aware, context-independent code search infrastructure

Over the last decade many code search engines and recommendation systems have been developed, both in academia and industry, to try to improve the component discovery step in the software reuse process. Key examples include Krugle, Koders, Portfolio, Merobase, Sourcerer, Strathcona and SENTRE. However, the recall and precision of this current generation of code search tools are limited by their inability to cope effectively with the structural dependencies between code units. This lack of “dependency awareness” manifests itself in three main ways. First, it limits the kinds of search queries that users can define and thus the precision and local recall of dependency aware searches (giving rise to large numbers of false positives and false negatives). Second, it reduces the global recall of the component harvesting process by limiting the range of dependency-containing software components that can be used to populate the search repository. Third, it significantly reduces the performance of the retrieval process for dependency-aware searches. This thesis lays the foundation for a new generation of dependency-aware code search engines that addresses these problems by designing and prototyping a new kind of software search platform. Inspired by the Merobase code search engine, this platform contains three main innovations - an enhanced, dependency aware query language which allows traditional Merobase interface-based searches to be extended with dependency requirements, a new “context independent” crawling infrastructure which can recognize dependencies between code units even when their context (e.g. project) is unknown, and a new graph-based database integrated with a full-text search engine and optimized to store code modules and their dependencies efficiently. After describing the background to, and state-of-the-art in, the field of code search engines and information retrieval the thesis motivates the aforementioned innovations and explains how they are realized in the DAISI (Dependency-Aware, context-Independent code Search Infrastructure) prototype using Lucene and Neo4J.DAISI is then used to demonstrate the advantages of the developed technology in a range of examples