Big amounts of test data generated by the current used software testing tools (QA-C/QA-C++ and Cantata) contain a variety of different values. The variances cause enormous challenges in data aggregation and interpretation that directly affect generation of test metrics. Due to the circumstance of data processing, this master thesis introduces a database-centric test management framework for test metrics aims at centrally handling the big data as well as facilitating the generation of test metrics. Each test result will be individually parsed to be a particular format before being stored in a centralized database. A friendly front-end user interface is connected and synchronized with the database that allows authorized users to interact with the stored data. With a granularity tracking mechanism, any stored data will be systematically located and programmatically interpreted by a test metrics generator to create various kinds of high-quality test metrics. The automatization of the framework is driven by Jenkins CI to automatically and periodically performing the sequential operations. The technology greatly and effectively optimizes and reduces effort in the development, as well as enhance the performance of the software testing processes. In this research, the framework is only started at managing the testing processes on software-unit level. However, because of the independence of the database from levels of software testing, it could also be expanded to support software development at any level.

Besides osteoconductivity and a high degradation rate, mesoporous bioactive glasses (MBGs) are specific for their highly ordered channel structure and high specific surface area, making them suitable as drug and/or growth factor delivery systems. On the other hand, the mesoporous channel structure and MBG composition can have an effect on common cell evaluation assays, leading to inconclusive results. This effect is especially important when MBG is mixed in composite bioinks, together with cells. Additionally, the hydrogel component of the ink can influence the degradation of MBG, leading to different ion releases, which can additionally affect the analyses. Hence, our aim here was to show how the MBG structure and composition influence common cell viability and differentiation assays when calcium (Ca)- or magnesium (Mg)-containing glass is part of an alginate-based composite bioink. We suggested pre-labeling of cells with DiI prior to bioprinting and staining with calcein-AM to allow identification of metabolically active cells expressing signals in both green and red channels, allowing the use of fluorescence imaging for cell viability evaluations in the presence of high amounts (7 wt %) of MBGs. The release and uptake of ions during degradation of CaMBG and MgMBG were significantly changed by alginate in the composite bioinks, as confirmed by higher release and uptake from bulk glasses. Additionally, we detected a burst release of Mg²⁺ from composites only after 24 h of incubation. Furthermore, we demonstrated that released ions and the mesoporous channel structure affect the measurement of lactate dehydrogenase (LDH) and alkaline phosphatase activity (ALP) in bioprinted composite scaffolds. Measured LDH activity was significantly decreased in the presence of CaMBG. On the other hand, the presence of MgMBG induced increased signal measured for the ALP. Taken together, our findings show how composite bioinks containing MBGs can interfere with common analyses, obtaining misleading results.

‘Data Imaginary’ is about the co-evolution of the literary and of data around the middle of the long nineteenth century. It argues that, during romanticism, US culture negotiated the outlines of the literary – what literature is, what literary value consists of, and what literature can do – in relation to the outlines of another representational project that was gaining sharper contours and a stronger foothold in public perception at the time: data. As the young nation was searching for a national literature of its own, data and data-driven practices formed an important foil, a conceptual resource to articulate the desire for a new, democratic literature. Revisiting formative decades of US literary self-perception through the conceptual lens of data, this book rethinks the representative project of transcendentalism, the catalog poetry of Walt Whitman, the formal experimentation of abolitionist literature, and the evolution of American (literary) studies.

Big amounts of test data generated by the current used software testing tools (QA-C/QA-C++ and Cantata) contain a variety of different values. The variances cause enormous challenges in data aggregation and interpretation that directly affect generation of test metrics. Due to the circumstance of data processing, this master thesis introduces a database-centric test management framework for test metrics aims at centrally handling the big data as well as facilitating the generation of test metrics. Each test result will be individually parsed to be a particular format before being stored in a centralized database. A friendly front-end user interface is connected and synchronized with the database that allows authorized users to interact with the stored data. With a granularity tracking mechanism, any stored data will be systematically located and programmatically interpreted by a test metrics generator to create various kinds of high-quality test metrics. The automatization of the framework is driven by Jenkins CI to automatically and periodically performing the sequential operations. The technology greatly and effectively optimizes and reduces effort in the development, as well as enhance the performance of the software testing processes. In this research, the framework is only started at managing the testing processes on software-unit level. However, because of the independence of the database from levels of software testing, it could also be expanded to support software development at any level.