Doctor of Philosophy / Department of Computing and Information Sciences / Matthew Dwyer / John M. Hatcliff / To analyze an open system, one needs to close it with a definition of its environment, i.e., its execution context. Environment modeling is a significant challenge: environment models should be general enough to permit analysis of large portions of a system's possible behaviors, yet sufficiently precise to enable cost-effective reasoning. This thesis presents the Bandera Environment Generator (BEG), a toolset that automates generation of environment models to provide a restricted form of modular model checking of Java programs, where the module's source code is the subject of analysis along with an abstract model of the environment's behavior. Since the most general environments do not allow for tractable model checking, BEG has support for restricting the environment behavior based on domain-specific knowledge and assumptions about the environment behavior, which can be acquired from a variety of sources. When the environment code is not available, developers can encode their assumptions as an explicit formal specification. When the environment code is available, BEG employs static analyses to extract environment assumptions. Both specifications and static analyses can be tuned to reflect domain-specific knowledge, i.e., to describe domain-specific aspects of the environment behavior. Initially, BEG was implemented to handle general Java applications; later, it was extended to handle two specific domains: Graphical User Interfaces (GUI) implemented using the Swing/AWT libraries and web applications implemented using the J2EE framework. BEG was evaluated on several non-trivial case studies, including industrial applications from NASA, SUN, and Fujitsu. This thesis presents the domain-specific environment generation for GUI and web applications and describes BEG, its extensible architecture, usage, and how it can be extended to handle new domains.

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The topic of this work is game environment generation from music. The main subject of this work is the music analysis. I am dealing with the problem of finding relevant information in music, which would be useful for game generating. The design of the system for music analysis, presented in this work, is based on the theory of signal processing and statistical classification. The proposed analysis of music is focused mainly on a beat detection, musical genre recognition and song segmentation. The second part of the work deals with the design of a game, which generates its environment from the data obtained in the music analysis. I have implemented the complete system for the music analysis and a prototype of the game, in which it is possible to evaluate the results from the analysis. The implementation and the achieved results are described in the conclusion of this work.