CS 172. Computers and Complexity
Current Schedule (Fall 2013)
Catalog Description: (4 units) Finite automata, Turing machines and RAMs. Undecidable, exponential, and polynomial-time problems. Polynomial-time equivalence of all reasonable models of computation. Nondeterministic Turing machines. Theory of NP-completeness: Cook's theorem, NP-completeness of basic problems. Selected topics in language theory, complexity and randomness.
Prerequisites: CS 170.
Course objectives: Provide a sound understanding of the fundamental limits of computation, as evidenced by the existence of non-computable functions, NP-hard problems etc. Formalize key abstract concepts such as machine models, language classes, universal machines, reducibility, computability, and resource-bounded computation. Understand how these concepts relate to practical issues such as compiler design, program checking, computational intractability, approximability and cryptography.
CS 172 presents some of the most fundamental results in theoretical Computer Science. These results attempt to answer, in a precise mathematical sense, the following two questions, which are of obvious practical as well as philosophical interest:
- Can a given problem be solved by computation?
- How efficiently can a given problem be solved by computation?
Thus, unlike CS 170, this course focuses on problems rather than on specific algorithms for solving problems. A precise formulation of the two questions above requires a formalization of the notion of "computer" or "machine". Thus the course outline breaks naturally into three parts:
- Models of computation (Automata Theory)
- Finite automata and regular languages.
- Push-down automata and context-free languages.
- Turing machines and recursive languages.
- What can we compute? (Computability Theory): existence of non-computable functions, the Halting problem, diagonalization, reductions, Rice¿s Theorem.
- How efficiently can we compute? (Complexity Theory): time- and space-bounded computation, the classes P and NP, NP-completeness, space-bounded computation (PSPACE and NL), provably exponential time languages, circuit complexity, zero knowledge proofs, applications to cryptography.