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Software testing in web services environment faces different challenges in comparison with testing in traditional software environments. Regression testing activities are triggered based on software changes or evolutions. In web services, evolution is not a choice for service clients. They have always to use the current updated version of the software. In addition test execution or invocation is expensive in web services and hence providing algorithms to optimize test case generation and execution is vital. In this environment, we proposed several approach for test cases' selection in web services' regression testing. Testing in this new environment should evolve to be included part of the service contract. Service providers should provide data or usage sessions that can help service clients reduce testing expenses through optimizing the selected and executed test cases.
Distributed systems comprise distributed computing systems, distributed information systems, and distributed pervasive systems. They are often very complex and their implementation is challenging. Intensive and continuous testing is indispensable to ensure reliability and high quality of a distributed system. The testing process should have a high degree of automation, not only on lower levels (i.e. unit and module testing), but also on higher testing levels (e.g. system, integration, and acceptance tests). To achieve automation on higher testing levels virtual infrastructure components (e.g. virtual machines, virtual networks) that are offered as a Service (IaaS) can be employed. The elasticity of on-demand computation resources fits well together with the varying resource demands of automated test execution.
A methodology for automated acceptance testing of distributed systems that uses virtual infrastructure is presented. It is founded on a task-oriented model that is used to abstract concurrency and asynchronous, remote communication in distributed systems. The model is used as groundwork for a domain-specific language that allows expressing tests for distributed systems in the form of scenarios. On the one hand, test scenarios are executable and, therefore, fully automated. On the other hand, test scenarios represent requirements to the system under test making an automated, example-based verification possible.
A prototypical implementation is used to apply the developed methodology in the context of two different case studies. The first case study uses RCE as an example of a distributed, workflow-driven integration environment for scientific computing. The second one uses MongoDB as an example of a document-oriented database system that offers distributed data storage through master-slave replication. The results of the experimental evaluation indicate that the developed acceptance testing methodology is a useful approach to design, build, and execute tests for distributed systems with high quality and a high degree of automation.
Automated parameterization of intermolecular pair potentials using global optimization techniques
(2014)
In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters’ influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.
The analysis of Δ9-tetrahydrocannabinol (THC) and its metabolites 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) from blood serum is a routine task in forensic toxicology laboratories. For examination of consumption habits, the concentration of the phase I metabolite THC-COOH is used. Recommendations for interpretation of analysis values in medical-psychological assessments (regranting of driver’s licenses, Germany) include threshold values for the free, unconjugated THC-COOH. Using a fully automated two-step liquid-liquid extraction, THC, 11-OH-THC, and free, unconjugated THC-COOH were extracted from blood serum, silylated with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and analyzed by GC/MS. The automation was carried out by an x-y-z sample robot equipped with modules for shaking, centrifugation, and solvent evaporation. This method was based on a previously developed manual sample preparation method. Validation guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh) were fulfilled for both methods, at which the focus of this article is the automated one. Limits of detection and quantification for THC were 0.3 and 0.6 μg/L, for 11-OH-THC were 0.1 and 0.8 μg/L, and for THC-COOH were 0.3 and 1.1 μg/L, when extracting only 0.5 mL of blood serum. Therefore, the required limit of quantification for THC of 1 μg/L in driving under the influence of cannabis cases in Germany (and other countries) can be reached and the method can be employed in that context. Real and external control samples were analyzed, and a round robin test was passed successfully. To date, the method is employed in the Institute of Legal Medicine in Giessen, Germany, in daily routine. Automation helps in avoiding errors during sample preparation and reduces the workload of the laboratory personnel. Due to its flexibility, the analysis system can be employed for other liquid-liquid extractions as well. To the best of our knowledge, this is the first publication on a comprehensively automated classical liquid-liquid extraction workflow in the field of forensic toxicological analysis.
In der heutigen Zeit nimmt die Bedeutung schlanker und effektiver Prozesse in Unternehmen vor dem Hintergrund des Wettbewerbs sowie Kostendrucks stetig zu. Um dieser Herausforderung entgegenzuwirken, fokussieren sich Unternehmen auf die Identifikation neuer innovativer Potenziale. Aufgrund der Tatsache, dass monotone und regelbasierte Prozesse durch Softwareroboter automatisiert werden können, ist das Interesse an Robotic Process Automation (RPA) in den letzten Jahren stetig gestiegen. Bevor sich Unternehmen allerdings für oder gegen den Einsatz von RPA entscheiden, ist es zunächst notwendig, dass die Entscheidungsträger ein Verständnis von RPA erlangen sowie die entsprechenden Einsatzpotenziale und Risiken einschätzen können. Dieser Artikel trägt diesem Bedürfnis Rechnung, indem es diese auf Basis einer Literaturrecherche ermittelt und bewertet. Im Ausblick wird das zukünftige Potenzial von RPA eingeschätzt.