This dissertation investigates the extraction of knowledge from a known environment. Virtual ontology – the extracted knowledge – is defined as a structure of a virtual environment with semantics. While many existing 3D reconstruction approaches can generate virtual environments without structure and related knowledge, the use of Metaearth architecture is proposed as a more descriptive data structure for virtual ontology. Its architecture consists of four layers: interactions and relationships between virtual components can be represented in the virtual space layer; and the library layers contribute to the design of large-scale virtual environments with less redundancy; and the mapping layer links the library layer to the virtual space layer; and the ontology layer functions as a context for the extracted knowledge. The dissertation suggests two construction methodologies. The first method generates a scene structure from a 2D image. Unlike other scene understanding techniques, the suggested method generates scene ontology without prior knowledge and human intervention. As an intermediate process, a new and effective fuzzy color-based over-segmentation method is suggested. The second method generates virtual ontology with 3D information using multi-view scenes. The many ambiguities in extracting 3D information are resolved by employing a new fuzzy dynamic programming method (FDP). The hybrid approach of FDP and 3D reconstruction method generates more accurate virtual ontology with 3D information. A virtual model is equipped with virtual ontology whereby contextual knowledge can be mapped into the Metaearth architecture via the proposed isomorphic matching method. The suggested procedure guarantees the automatic and autonomous processing demanded in virtual interaction analysis with far less effort and computational time.

Modern software is built by teams of developers that work in a collaborative environment. The goal of this kind of development is that multiple developers can work in parallel. They can alter a set of shared artifacts and inspect and integrate the source code changes of other developers. For example, bug fixes, enhancements, new features or adaptations due to changing environment might be integrated into the system release. At a technical level, a collaborative development process is supported by version control systems. Since these version control systems allow developers to work in their own branch, merging and integration have become an integral part of the development process. These systems use automatic and advanced merging techniques to help developers to merge their modifications in the development repositories. However, these techniques do not guarantee to have a functional system. While the use of branching in the development process offers numerous advantages, the activity of merging and integrating changes is hampered by the lack of comprehensive support to assist developers in these activities. For example, the integration of changes can have an unexpected impact on the design or behavior of the system, leading to the introduction of subtle bugs. Furthermore, developers are not supported when integrating changes across branches (cherry picking), when dealing with branches that have diverged, when finding the dependencies between changes, or when assessing the potential impact of changes. In this dissertation we present an approach that aims at alleviating these problems by providing developers and, more precisely, integrators with semi-automated support for assisted integration within a branch and across branches. We focus on helping integrators with their information needs when understanding and integrating changes by means of characterizations of changes and streams of changes (i.e., sequence of successive changes within a branch) together with their dependencies. These characterizations rely on the first-class representation of systems' histories and changes based on program entities and their relationships rather than on files and text. For this, we provide a family of meta-models (Ring, RingH, RingS and RingC) that offer us the representation of program entities, systems' histories, changes and their dependencies, along with analyses for version comparison, and change and dependency identification. Instances of these meta-models are then used by our proposed tool support to enable integrators to analyze the characterizations and changes. Torch, a visual tool, and JET, a set of tools, actually provide the information needs to assist integration within a branch and across branches by means of the characterization of changes and streams of changes respectively.