Accelerated test execution using GPUs

As product life-cycles become shorter and the scale and complexity of systems increase, accelerating the execution of large test suites gains importance. Existing research has primarily focussed on techniques that reduce the size of the test suite. By contrast, we propose a technique that accelerates test execution, allowing test suites to run in a fraction of the original time, by parallel execution with a Graphics Processing Unit (GPU). Program testing, which is in essence execution of the same program with multiple sets of test data, naturally exhibits the kind of data parallelism that can be exploited with GPUs. Our approach simultaneously executes the program with one test case per GPU thread. GPUs have severe limitations, and we discuss these in the context of our approach and define the scope of our applications. We observe speed-ups up to a factor of 27 compared to single-core execution on conventional CPUs with embedded systems benchmark programs

Some Findings Concerning Requirements in Agile Methodologies

gile methods have appeared as an attractive alternative to conventional methodologies. These methods try to reduce the time to market and, indirectly, the cost of the product through flexible development and deep customer involvement. The processes related to requirements have been extensively studied in literature, in most cases in the frame of conventional methods. However, conclusions of conventional methodologies could not be necessarily valid for Agile; in some issues, conventional and Agile processes are radically different. As recent surveys report, inadequate project requirements is one of the most conflictive issues in agile approaches and better understanding about this is needed. This paper describes some findings concerning requirements activities in a project developed under an agile methodology. The project intended to evolve an existing product and, therefore, some background information was available. The major difficulties encountered were related to non-functional needs and management of requirements dependencies

Metastable Corundum-Type In2O3: Phase Stability, Reduction Properties, and Catalytic Characterization

The phase stability, reduction, and catalytic properties of corundum-type rhombohedral In2O3 have been comparatively studied with respect to its thermodynamically more stable cubic In2O3 counterpart. Phase stability and transformation were observed to be strongly dependent on the gas environment and the reduction potential of the gas phase. As such, reduction in hydrogen caused both the efficient transformation into the cubic polymorph as well as the formation of metallic In especially at high reduction temperatures between 573 and 673 K. In contrast, reduction in CO suppresses the transformation into cubic In2O3 but leads to a larger quantity of In metal at comparable reduction temperatures. This difference is also directly reflected in temperature-dependent conductivity measurements. Catalytic characterization of rh-In2O3 reveals activity in both routes of the water-gas shift equilibrium, which gives rise to a diminished CO2-selectivity of 60% in methanol steam reforming. This is in strong contrast to its cubic counterpart where CO2 selectivities of close to 100% due to the suppressed inverse water-gas shift reaction, have been obtained. Most importantly, rh-In2O3 in fact is structurally stable during catalytic characterization and no unwanted phase transformations are triggered. Thus, the results directly reveal the application-relevant physicochemical properties of rh-In2O3 that might encourage subsequent studies on other less-common In2O3 polymorphs.(VLID)2581066Accepted versio

Silicon oxycarbonitride ceramic containing nickel nanoparticles from design to catalytic application

Nickel containing silicon oxycarbonitride ceramic nanocomposites are synthesized from hydrous nickel acetate and poly vinyl silazane Durazane 1800 or perhydropolysilazane NN120 20 A PHPS . A room temperature chemical reaction results in Ni containing polysilazane precursors which are transformed into ceramic nanocomposites with nickel nanoparticles 2 4 nm upon pyrolysis at elevated temperatures 700 1100 C under an argon atmosphere. The ceramic nanocomposites derived from the Durazane 1800 Ni precursor by the thermolysis process at 700 and 900 C manifest a microporous structure with a BET specific surface area of amp; 8764;361 and amp; 8764;232 m2 g amp; 8722;1, respectively. In contrast, all pyrolyzed samples derived from the PHPS Ni precursor exhibit a nonporous structure. The Ni SiOCN ceramic nanocomposites tested in a plug flow fixed bed reactor display significant catalytic activity in dry methane reforming to syngas. The highest CH4 reaction rate of 0.18 mol min amp; 8722;1 gNi amp; 8722;1 is observed at 800 C for the sample derived from the PHPS Ni precursor by pyrolysis at 900 C. All these make the materials developed in this work, i.e. nickel nanoparticles in situ formed in the SiOCN ceramic matrix, as promising candidates for heterogeneous catalysi

The application of a real-time rapid-prototyping environment for the behavioral rehabilitation of a lost function in rats

Abstract-In this paper we propose a Rapid Prototyping Environment (RPE) for real-time biosignal analysis including ECG, EEG, ECoG and EMG of humans and animals requiring a very precise time resolution. Based on the previous RPE which was mainly designed for developing Brain Computer Interfaces (BCI), the present solution offers tools for data preprocessing, analysis and visualization even in the case of high sampling rates and furthermore tools for precise cognitive stimulation. One application of the system, the analysis of multi-unit activity measured from the brain of a rat is presented to prove the efficiency of the proposed environment. The experimental setup was used to design and implement a biomimetic, biohybrid model for demonstrating the recovery of a learning function lost with age. Throughout the paper we discuss the components of the setup, the software structure and the online visualization. At the end we present results of a real-time experiment in which the model of the brain learned to react to the acquired signals

Quality requirements in large-scale distributed agile projects - A systematic literature review

Context and Motivation: Agile development methods have become increasingly popular in the last years. However, these methods hardly pay attention to quality requirements (QRs), which could undermine the profits of fast delivery by introducing high rework efforts later on. This risk is high especially in agile large-scale distributed settings. Question/problem: Although several publications reported on the insufficient attention to quality requirements in agile methods, still little is known about agile requirements engineering practices and their impact on quality requirements in large-scale distributed settings. However, companies increasingly use agile methods in those settings, where the negative impact of ignoring quality requirements is large. Hence, the goal of this study is to identify the challenges in the engineering of quality requirements in large-scale distributed agile projects that have been researched so far, the agile practices that have contributed to the emergence of these challenges, and the proposed solutions. Principle ideas/results: Following an evidence-based research method, we examined 60 papers on quality requirements in agile. We found that, while there are multiple proposals to engineer quality requirements in agile, none of those has been tried out in real-life settings. Evaluating scalability of these proposals, therefore, is a priority for future research. Contribution: This paper identified 12 challenges in agile projects that harm the quality requirements. Besides, we identified and evaluated 13 proposals for dealing with quality requirements in agile projects, along with implications for practice and research