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Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets. Preclinical imaging, such as micro-magnetic resonance imaging (μMRI) can produce tomographic datasets of murine vasculature across length scales and organs, which is of outmost importance to study tumor progression, angiogenesis, or vascular risk factors for diseases such as Alzheimer’s. Training a neural network capable of accurate segmentation results requires a sufficiently large amount of labelled data, which takes a long time to compile. Recently, several reasonably automated approaches have emerged in the preclinical context but still require significant manual input and are less accurate than the deep learning approach presented in this paper—quantified by the Dice score. In this work, the implementation of a shallow, three-dimensional U-Net architecture for the segmentation of vessels in murine brains is presented, which is (1) open-source, (2) can be achieved with a small dataset (in this work only 8 μMRI imaging stacks of mouse brains were available), and (3) requires only a small subset of labelled training data. The presented model is evaluated together with two post-processing methodologies using a cross-validation, which results in an average Dice score of 61.34% in its best setup. The results show, that the methodology is able to detect blood vessels faster and more reliably compared to state-of-the-art vesselness filters with an average Dice score of 43.88% for the used dataset.
While Virtual Reality (VR) has been applied to various domains to provide new visualization and interaction capabilities, enabling programmers to utilize VR for their software development and maintenance tasks has been insufficiently explored. In this paper, we present the Hyper-Display Environment (HyDE) in the form of a mixed-reality (HyDE-MR) or virtual reality (HyDE-VR) variant respectively, which provides simultaneous multiple operating system window visualization with integrated keyboard/mouse viewing and interaction using MR or in pure VR via a virtual keyboard. This paper applies HyDE in a software development case study as an alternative to typical non-VR Integrated Development Environments (IDEs), supporting software engineering tasks with multiple live screens in VR as an augmented virtuality. The MR solution concept enables programmers to benefit from VR visualization and virtually unlimited information displays while supporting their more natural keyboard interaction for basic code-centric tasks. Thus, developers can leverage VR paradigms and capabilities while directly interacting with their favorite tools to develop and maintain program code. A prototype implementation is described, with a case study demonstrating its feasibility and an initial empirical study showing its potential.
Enterprise Architecture (EA) Frameworks (EAFs) have attempted to support comprehensive and cohesive modeling and documentation of the enterprise. However, these EAFs were not conceived for today’s rapidly digitalized enterprises and the associated IT complexity. A digitally-centric EAF is needed, freed from the past restrictive EAF paradigms and embracing the new potential in a data-centric world. This paper proposes an alternative EAF that is digital, holistic, and digitally sustainable - the Digital Diamond Framework. D2F is designed for responsive and agile enterprises, for aligning business plans and initiatives with the actual enterprise state, and addressing the needs of EA for digitized structure, order, modeling, and documentation. The feasibility of D2F is demonstrated with a prototype implementation of an EA tool that applies its principles, showing how the framework can be practically realized, while a case study based on ArchiSurance example and an initial performance and scalability characterization provide additional insights as to its viability.
Databases are becoming an ubiquitous and integral part of most software as the data era and the Internet of Everything unfolds. Alternative database types such as NoSQL grow in popularity and allow data to be stored and accessed more simply or in new ways. Thus, software developers, not just database specialists, are more likely to encounter and need to deal with databases. Virtual Reality (VR) technology has grown in popularity, yet its integration in the software development tool chain has been limited. One potential application area for VR technology that has not been sufficiently explored is database-model visualization. This paper describes Virtual Reality Immersion in Data Models (VRiDaM), a generic database-model approach for visualizing, navigating, and conveying database-model information interactively. It describes and explores both native VR and WebVR solution concepts, with prototypes showing the viability of the approach.
The volume of program source code created, reused, and maintained worldwide is rapidly increasing, yet code comprehension remains a limiting productivity factor. For developers and maintainers, well known common software design patterns and the abstractions they offer can help support program comprehension. However, manual pattern documentation techniques in code and code-related assets such as comments, documents, or models are not necessarily consistent or dependable and are cost-prohibitive. To address this situation, we propose the Hybrid Design Pattern Detection (HyDPD), a generalized approach for detecting patterns that is programming-language-agnostic and combines graph analysis (GA) and Machine Learning (ML) to automate the detection of design patterns via source code analysis. Our realization demonstrates its feasibility. An evaluation compared each technique and their combination for three common patterns across a set of 75 single pattern Java and C# public sample pattern projects. The GA component was also used to detect the 23 Gang of Four design patterns across 258 sample C# and Java projects as well as in a large Java project. Performance and scalability were measured. The results show the advantages and potential of a hybrid approach for combining GA with artificial neural networks (ANN) for automated design pattern detection, providing compensating advantages such as reduced false negatives and improved F1 scores.
VR-V&V
(2023)
To build quality into a software (SW) system necessitates supporting quality-related lifecycle activities during the software development. In software engineering, software Verification and Validation (V&V) processes constitute an inherent part of Software Quality Assurance (SQA) processes. A subset of the V&V activities involved are: 1) bidirectional traceability analysis of requirements to design model elements, and 2) software testing. Yet the complex nature of large SW systems and the dependencies involved in both design models and testing present a challenge to current V&V tools and methods regarding support for trace analysis. One of software’s essential challenges remains its invisibility, which also affects V&V activities. This paper contributes VR-V&V, a Virtual Reality (VR) solution concept towards supporting immersive V&V activities. By visualizing requirements, models, and testing artifacts with dependencies and trace relations immersively, they are intuitively accessible to a larger stakeholder audience such as SQA personnel while supporting digital cognition. Our prototype realization shows the feasibility of supporting immersive bidirectional traceability as well as immersive software test coverage and analysis. The evaluation results are based on a case study demonstrating its capabilities, in particular traceability support was performed with ReqIF, ArchiMate models, test results, test coverage, and test source to test target dependencies.
VR-SysML+Traceability
(2023)
As systems grow in complexity, the interdisciplinary nature of systems engineering makes the visualization and comprehension of the underlying system models challenging for the various stakeholders. This, in turn, can affect validation and realization correctness. Furthermore, stakeholder collaboration is often hindered due to the lack of a common medium to access and convey these models, which are often partitioned across multiple 2D diagrams. This paper contributes VR-SysML, a solution concept for visualizing and interacting with Systems Modeling Language (SysML) models in Virtual Reality (VR). Our prototype realization shows its feasibility, and our evaluation results based on a case study shows its support for the various SysML diagram types in VR, cross-diagram element recognition via our Backplane Followers concept, and depicting further related (SysML and non-SysML) models side-by-side in VR.