Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

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Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem.

Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem.