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Web application testing is an active research area. Garousi et al. did a systematic mapping study and classified 79 papers published between 2000-2011. However, there seems to be a lack of information exchange between the scientific community and tool developers.
This thesis systematically analyzes the field of functional, system level web application testing tools. 194 candidate tools were collected in the tool search and screened, with 23 tools being selected as foundation of this thesis. These 23 tools were systematically used to generate a feature model of the domain. The methodology to support this is an additional contribution of this thesis. It processes end user documentation of tools belonging to an examined domain and creates a feature model. The feature model gives an overview over the existing features, their alternatives and their distribution. It can be used to identify trends and problems, extraordinary features, help decision making of tool purchase or guide scientists how to focus research.
Global crop production increased substantially in recent decades due to agricultural intensification and expansion and today agricultural areas occupy about 38% of Earth’s terrestrial surface - the largest use of land on the planet. However, current high-intensity agricultural practices fostered in the context of the Green Revolution led to serious consequences for the global environment. Pesticides, in particular, are highly biologically active substances that can threaten the ecological integrity of aquatic and terrestrial ecosystems. Although the global pesticide use increases steadily, our field-data based knowledge regarding exposure of non-target ecosystems such as surface waters is very restricted. Available studies have by now been limited to spatially restricted geographical areas or had rather specific objectives rendering the extrapolation to larger spatial scales questionable.
Consequently, this thesis evaluated based on four scientific publications the exposure, effects, and regulatory implications of particularly toxic insecticides` concentrations detected in global agricultural surface waters. FOCUS exposure modelling was used to characterise the highly specific insecticide exposure patterns and to analyse the resulting implications for both monitoring and risk assessment (publication I). Based on more than 200,000 scientific database entries, 838 peer-reviewed studies finally included, and more than 2,500 sites in 73 countries, the risks of agricultural insecticides to global surface waters were analysed by means of a comprehensive meta-analysis (publication II). This meta-analysis evaluated whether insecticide field concentrations exceed legally accepted regulatory threshold levels (RTLs) derived from official EU and US pesticide registration documents and, amongst others, how risks depend on insecticide development over time and stringency of environmental regulation. In addition, an in-depth analysis of the current EU pesticide regulations provided insights into the level of protection and field relevance of highly elaborated environmental regulatory risk assessment schemes (publications III and IV).
The results of this thesis show that insecticide surface water exposure is characterized by infrequent and highly transient concentration peaks of high ecotoxicological relevance. We thus argue in publication I that sampling based on regular intervals is inadequate for the detection of insecticide surface water concentrations and that traditional risk assessment concepts based on all insecticide concentrations including non-detects lead to severely biased results and critical underestimations of risks. Based on these considerations, publication II demonstrates that out of 11,300 measured insecticide concentrations (MICs; i.e., those actually detected and quantified), 52.4% (5,915 cases; 68.5%) exceeded the RTL for either water (RTLSW) or sediments. This indicates a substantial risk for the biological integrity of global water resources as additional analyses on pesticide effects in the field clearly evidence that the regional aquatic biodiversity is reduced by approximately 30% at pesticide concentrations equalling the RTLs. In addition, publication II shows that there is a complete lack of scientific monitoring data for ~90% of global cropland and that both the actual insecticide contamination of surface waters and the resulting ecological risks are most likely even greater due to, for example, inadequate sampling methods employed in the studies and the common occurrence of pesticide mixtures. A linear model analysis identified that RTLSW exceedances depend on the catchment size, sampling regime, sampling date, insecticide substance class, and stringency of countries` environmental regulations, as well as on the interactions of these factors. Importantly, the risks are significantly higher for newer-generation insecticides (i.e., pyrethroids) and are high even in countries with stringent environmental regulations. Regarding the latter, an analysis of the EU pesticide regulations revealed critical deficiencies and the lack of protectiveness and field-relevance for current presumed highly elaborated FOCUS exposure assessment (publication IV) and overall risk assessment schemes (publication III). Based on these findings, essential risk assessment amendments are proposed.
In essence, this thesis analyses the agriculture–environment linkages for pesticides at the global scale and it thereby contributes to a new research frontier in global ecotoxicology. The overall findings substantiate that agricultural insecticides are potential key drivers for the global freshwater biodiversity crisis and that the current regulatory risk assessment approaches for highly toxic anthropogenic chemicals fail to protect the global environment. This thesis provides an integrated view on the environmental side effects of global high-intensity agriculture and alerts that beside worldwide improvements to current pesticide regulations and agricultural pesticide application practices, the fundamental reformation of conventional agricultural systems is urgently needed to meet the twin challenges of providing sufficient food for a growing human population without destroying the ecological integrity of global ecosystems essential to human existence.
The formulation of the decoding problem for linear block codes as an integer program (IP) with a rather tight linear programming (LP) relaxation has made a central part of channel coding accessible for the theory and methods of mathematical optimization, especially integer programming, polyhedral combinatorics and also algorithmic graph theory, since the important class of turbo codes exhibits an inherent graphical structure. We present several novel models, algorithms and theoretical results for error-correction decoding based on mathematical optimization. Our contribution includes a partly combinatorial LP decoder for turbo codes, a fast branch-and-cut algorithm for maximum-likelihood (ML) decoding of arbitrary binary linear codes, a theoretical analysis of the LP decoder's performance for 3-dimensional turbo codes, compact IP models for various heuristic algorithms as well as ML decoding in combination with higher-order modulation, and, finally, first steps towards an implementation of the LP decoder in specialized hardware. The scientific contributions are presented in the form of seven revised reprints of papers that appeared in peer-reviewed international journals or conference proceedings. They are accompanied by an extensive introductory part that reviews the basics of mathematical optimization, coding theory, and the previous results on LP decoding that we rely on afterwards.
Traditional Driver Assistance Systems (DAS) like for example Lane Departure Warning Systems or the well-known Electronic Stability Program have in common that their system and software architecture is static. This means that neither the number and topology of Electronic Control Units (ECUs) nor the presence and functionality of software modules changes after the vehicles leave the factory.
However, some future DAS do face changes at runtime. This is true for example for truck and trailer DAS as their hardware components and software entities are spread over both parts of the combination. These new requirements cannot be faced by state-of-the-art approaches of automotive software systems. Instead, a different technique of designing such Distributed Driver Assistance Systems (DDAS) needs to be developed. The main contribution of this thesis is the development of a novel software and system architecture for dynamically changing DAS using the example of driving assistance for truck and trailer. This architecture has to be able to autonomously detect and handle changes within the topology. In order to do so, the system decides which degree of assistance and which types of HMI can be offered every time a trailer is connected or disconnected. Therefore an analysis of the available software and hardware components as well as a determination of possible assistance functionality and a re-configuration of the system take place. Such adaptation can be granted by the principles of Service-oriented Architecture (SOA). In this architectural style all functionality is encapsulated in self-contained units, so-called Services. These Services offer the functionality through well-defined interfaces whose behavior is described in contracts. Using these Services, large-scale applications can be built and adapted at runtime. This thesis describes the research conducted in achieving the goals described by introducing Service-oriented Architectures into the automotive domain. SOA deals with the high degree of distribution, the demand for re-usability and the heterogeneity of the needed components.
It also applies automatic re-configuration in the event of a system change. Instead of adapting one of the frameworks available to this scenario, the main principles of Service-orientation are picked up and tailored. This leads to the development of the Service-oriented Driver Assistance (SODA) framework, which implements the benefits of Service-orientation while ensuring compatibility and compliance to automotive requirements, best-practices and standards. Within this thesis several state-of-the-art Service-oriented frameworks are analyzed and compared. Furthermore, the SODA framework as well as all its different aspects regarding the automotive software domain are described in detail. These aspects include a well-defined reference model that introduces and relates terms and concepts and defines an architectural blueprint. Furthermore, some of the modules of this blueprint such as the re-configuration module and the Communication Model are presented in full detail. In order to prove the compliance of the framework regarding state-of-the-art automotive software systems, a development process respecting today's best practices in automotive design procedures as well as the integration of SODA into the AUTOSAR standard are discussed. Finally, the SODA framework is used to build a full-scale demonstrator in order to evaluate its performance and efficiency.
Software systems are often developed as a set of variants to meet diverse requirements. Two common approaches to this are "clone-and-owning" and software product lines. Both approaches have advantages and disadvantages. In previous work we and collaborators proposed an idea which combines both approaches to manage variants, similarities, and cloning by using a virtual platform and cloning-related operators.
In this thesis, we present an approach for aggregating essential metadata to enable a propagate operator, which implements a form of change propagation. For this we have developed a system to annotate code similarities which were extracted throughout the history of a software repository. The annotations express similarity maintenance tasks, which can then either be executed automatically by propagate or have to be performed manually by the user. In this work we outline the automated metadata extraction process and the system for annotating similarities; we explain how the implemented system can be integrated into the workflow of an existing version control system (Git); and, finally, we present a case study using the 101haskell corpus of variants.
A fundamental understanding of attachment of engineered nanoparticles to environmentalrnsurfaces is essential for the prediction of nanoparticle fate and transport in the environment.
The present work investigates the attachment of non-coated silver nanoparticles and citraterncoated silver nanoparticles to different model surfaces and environmental surfaces in thernpresence and absence of humic acid. Batch sorption experiments were used for this investigation.
The objective of this thesis was to investigate how silver nanoparticles interactrnwith surfaces having different chemical functional groups. The effect of presence of HA, on the particle-surface interactions was also investigated. In the absence of humic acid, nanoparticle-surface interactions or attachment was influencedrnby the chemical nature of the interacting surfaces. On the other hand, in the presence ofrnhumic acid, nanoparticle-surface attachment was influenced by the specific surface area of the sorbent surfaces. The sorption of non-coated silver nanoparticles and citrate coatedrnnanoparticles to all the surfaces was nonlinear and best described by Langmuir isotherm, indicating monolayer sorption of nanoparticles on to the surfaces. This can be explained as due to the blocking effect generated by the particle-particle repulsion. In the presence of humic acid, sorption of nanoparticles to the surfaces was linear. When the humic acid was present in the interacting medium, both the nanoparticles and surfaces were getting coated with humic acid and this masks the chemical functionalities of the surfaces. This leads to the change in particle-surface interactions, in the presence of humic acid. For the silver nanoparticle sorption from an unstable suspension, the sorption isotherms did not follow any classical sorption models, suggesting interplay between aggregation and sorption. Citrate coated silver nanoparticles and humic acid coated silver nanoparticles showed arndepression in sorption compared to the sorption of non-coated silver nanoparticles. In therncase of citrate coated silver nanoparticles the decrease in sorption can be explained by thernmore negative zeta potential of citrate coated nanoparticles compared to non-coated ones. For humic acid coated nanoparticles the sorption depression can be due to the steric hindrance caused by the free humic acid molecules which may coat the sorbent surface or due to the competition for sorption sites between the nanoparticle and free humic acid molecules present in the suspension. Thus nanoparticle surface chemistry is an important factor that determines the attachment of nanoparticles towards surfaces and it makes the characterization of nanoparticle surface an essential step in the study of their fate in the environment.
Another aim of this study was to introduce the potential of chemical force microscopy for nanoparticle surface characterization. With the use of this technique, it was possible to distinguish between bare silver nanoparticles, citrate coated silver nanoparticles, and humic acid coated silver nanoparticles. This was possible by measuring the adhesion forces between the nanoparticles and five different AFM probes having different chemical functionalization.
Change of ecosystems and the associated loss of biodiversity is among the most important environmental issues. Climate change, pollution, and impoundments are considered as major drivers of biodiversity loss. Organism traits are an appealing tool for the assessment of these three stressors, due to their ability to provide mechanistic links between organism responses and stressors, and consistency over wide geographical areas.
Additionally, traits such as feeding habits influence organismal performance and ecosystem processes. Although the response of traits of specific taxonomic groups to stressors is known, little is known about the response of traits of different taxonomic groups to stressors. Additionally, little is known about the effects of small impoundments on stream ecosystem processes, such as leaf litter decomposition, and food webs.
After briefly introducing the theoretical background and objectives of the studies, this thesis begins by synthesizing the responses of traits of different taxonomic groups to climate change and pollution. Based on 558 peer-reviewed studies, the uniformity (i.e., convergence) in trait response across taxonomic groups was evaluated through meta-analysis (Chapter 2). Convergence was primarily limited to traits related to tolerance.
In Chapter 3, the hypothesis that small impoundments would modify leaf litter decomposition rates at the sites located within the vicinity of impoundments, by altering habitat variables and invertebrate functional feeding groups (FFGs) (i.e., shredders), was tested. Leaf litter decomposition rates were significantly reduced at the study sites located immediately upstream (IU) of impoundments, and were significantly related to the abundance of invertebrate shredders.
In Chapter 4, the invertebrate FFGs were used to evaluate the effect of small impoundments on stream ecosystem attributes. The results showed that heterotrophic production was significantly reduced at the sites IU. With regard to food webs, the contribution of methane gas derived carbon to the biomass of chironomid larvae was evaluated through correlation of stable carbon isotope values of chironomid larvae and methane gas concentrations.
The results indicated that the contribution of methane gas derived carbon into stream benthic food web is low. In conclusion, traits are a useful tool in detecting ecological responses to stressors across taxonomic groups, and the effects of small impoundments on stream ecological integrity and food web are limited.
The increasing application of titanium dioxide nanoparticles (nTiO2) entails an increased risk regarding their release to surface water bodies, where they likely co-occur with other anthropogenic stressors, such as heavy metals. Their co-occurrence may lead to an adsorption of the metal ions onto the particles. These nanoparticles often sediment, due to their agglomeration, and thus pose a risk for pelagic or benthic species. The combined toxicity of nTiO2 and heavy metals is likely influenced by the properties of both stressors (since they may alter their interaction) and by environmental parameters (e.g., organic matter, pH, ionic strength) affecting their fate.
These issues were not yet systematically examined by the recent literature. Therefore, this thesis investigated the influence of nTiO2-products with differing crystalline phase composition on the toxicity of copper (as representative for heavy metals) in presence of different organic matters using the pelagic test organism Daphnia magna.
Moreover, the duration of the stressors` interaction (=aging) likely modulates the combined toxicity. Hence, the influence of nTiO2 on copper toxicity after aging as a function of environmental parameters (i.e., organic matter, pH, ionic strength) was additionally investigated.
Finally, the transferability of the major findings to benthic species was examined using Gammarus fossarum. The present thesis discovered a reduction of the copper toxicity facilitated by nTiO2 for all assessed scenarios, while its magnitude was determined by the surface area and structure of nTiO2, the quantity and quality of organic matter as well as the aging of both stressors. The general copper toxicity reduction by nTiO2 was also transferable to benthic species, despite their potentially increased exposure due to the sedimentation of nTiO2 with adsorbed copper. These observations suggest the application of nTiO2 as remediation agent, but potential side effects (e.g., chronic toxicity, reactive oxygen species formation) require further investigations. Moreover, questions regarding the transferability to other stressors (e.g., different heavy metals, organic chemicals) and the fate of stressors adsorbed to nTiO2 in aquatic ecosystems remain open.
Information systems research has started to use crowdsourcing platforms such as Amazon Mechanical Turks (MTurk) for scientific research, recently. In particular, MTurk provides a scalable, cheap work-force that can also be used as a pool of potential respondents for online survey research. In light of the increasing use of crowdsourcing platforms for survey research, the authors aim to contribute to the understanding of its appropriate usage. Therefore, they assess if samples drawn from MTurk deviate from those drawn via conventional online surveys (COS) in terms of answers in relation to relevant e-commerce variables and test the data in a nomological network for assessing differences in effects.
The authors compare responses from 138 MTurk workers with those of 150 German shoppers recruited via COS. The findings indicate, inter alia, that MTurk workers tend to exhibit more positive word-of mouth, perceived risk, customer orientation and commitment to the focal company. The authors discuss the study- results, point to limitations, and provide avenues for further research.
Code package managers like Cabal track dependencies between packages. But packages rarely use the functionality that their dependencies provide. This leads to unnecessary compilation of unused parts and to speculative conflicts between package versions where there are no conflicts. In two case studies we show how relevant these two problems are. We then describe how we could avoid them by tracking dependencies not between packages but between individual code fragments.