MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted.

Understanding Michigan nonindustrial private forest landowners attitudes and knowledge about forest management

Approximately one-fourth of the non-industrial private forestland (NIPF) owners in the state of Michigan, who collectively own approximately 50% of the private forested land, have conducted commercial timber harvest in recent years. Previous studies indicated that NIPFs preferred to manage their forest for a sustained yield of high-quality timber, but were limited to even-aged regeneration treatments or conversion for uneven-aged silviculture due to previous cuttings. Improved knowledge about NIPF’s intentions and forest management behavior could be useful for successful implementation of sustained yield management. This study’s objective was to identify more active NIPF’s attitudes towards timber management, their forest management practices and whether their forest management behavior leads or leads not to q management for sustained yield. Active NIPF’s intentions to harvest timber for biofuels and its suitability with NIPF’s forest management behavior will be discussed. Phone interviews of 30 NIPFs who have experience with commercial timber harvests were conducted between August and October 2011. All interviews were recorded, transcribed, and analyzed for identifying NIPF’s motivations, attitudes, forest management behavior and forestry related knowledge. Interviewees, whether consciously or not, tended to manage their land for a sustained yield and they would be willing to harvest timber for biofuels facility as long as it benefits landowners management goals.