Semester
Spring
Date of Graduation
2010
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Lane Department of Computer Science and Electrical Engineering
Committee Chair
Tim Menzies
Abstract
Solutions to non-linear requirements engineering problems may be "brittle"; i.e. small changes may dramatically alter solution effectiveness. Hence, it is not enough to just generate solutions to requirements problems---we must also assess solution robustness. This thesis aims to address two concerns: (a) Is demonstrating robustness a time consuming task? and (b) Is it necessary that solution quality be traded off against solution robustness?;Using a Bayesian ranking heuristic, the KEYS2 algorithm fixes a small number of important variables, rapidly pushing the search into a stable, optimal plateau. By design, KEYS2 generates decision ordering diagrams (in time experimentally shown to be O(N2)). Once generated, these diagrams can confirm solution robustness in linear time. When assessed in terms of reducing inference times, increasing solution quality, and decreasing the variance of the generated solution, KEYS2 out-performs other search algorithms (simulated annealing, A*, MaxWalkSat).
Recommended Citation
Gay, Gregory, "The robust optimization of non-linear requirements models" (2010). Graduate Theses, Dissertations, and Problem Reports. 4595.
https://researchrepository.wvu.edu/etd/4595