CAREER: Algorithms for Self-testing/Correcting Program and Learning

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This project focuses on two lines of research: (1) program correctness and (2) the problem of learning deterministic and probabilistic finite automata:(1) Because the simplest of programs can be full of elusive errors, the study of program checkers, self-testing programs and self correcting programs, was introduced, in order to permit the use of a program without trusting that it works correctly. In this area, the goal of this project is to develop a core of algorithmic techniques for writing fast and simple checkers, self-correctors, and self-testers;(2) The goal in the area of learning deterministic and probabilistic finite automata is to study the applications of automata learning algorithms to on-line page replacement strategies, reinforcement learning, game theory, part-of-speech tagging, phoneme modeling, and parsing. The Integrated Educational Plan of this CAREER Grant includes designing new projects to facilitate undergraduate and graduate student involvement in the research process and mentoring undergraduates. ***