CS1303-THEORY OF COMPUTATION PDF

Department: Computer Science and Engineering Subject Code/Name: CS – Theory of Computation Document Type: Question Bank Website: niceindia. Theory of Computation Anna university Question paper Month/year Subject Download link May / June QP: TOC. Anna University B E /B Tech Examination May/June Department of CSE Fifth Semester CS Theory of Computation Question paper.

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Introduction to Turing machines; recursive functions; undecidability. Choice of one of three: Covers advanced techniques for analyzing recursive algorithms, examines major algorithm-design approaches including greedy, divide and conquer, dynamic programming, and graph-based approaches.

A “theory” course is any course, taught by any department, that is mainly: Introduction to parallel computational models and algorithms. Course details at http: Their advising material says those who want to do an honours degree but don’t have any specialty in mind should take this option.

Introduction to soundness, completeness and decidability. Strings and pattern matching. Students will be expected to show good design principles and adequate skills at reasoning about the correctness and complexity of algorithms.

CR: Survey of theory requirements in other Canadian Honours programs – Soma-notes

Topics include their representation, uses, and algorithms for their traversal and manipulation. Topics covered include graph theory, trees, inclusion-exclusion, generating functions, recurrence relations, and optimization and matching. CS Discrete Computational Structures Finite and discrete algebraic structures computxtion to computers; sets, functions, relations. Machines and Algorithms The first part develops and analyzes some standard techniques for algorithm development which are widely applicable to computer science problems.

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Algorithm design paradigms like divide-and-conquer, dynamic programming, greedy, external sorting, B-trees. Topics which will be studied include: No required theory courses – third year choices will be limited without at least the second-year algorithms course Algorithms I which is a somewhat a combo of and Theory of Computation Finite Automata, regular expressions and languages; properties of regular languages; context-free grammars and languages; pushdown automata; properties of context-free languages.

The second part analyzes several formal models of computers so that their capabilities are known. Boolean algebra and combinations logic circuits; proof techniques; functions and sequential circuits; sets and relations; finite state machines; sequential instruction execution.

CS Theory of Computation ( R) May/June Question paper

Random access machine model. Worst-case, average-case, and best-case analysis. What are the components of Finite automaton model? This was counted as a theory course if all the choices were theory by our definition, e.

It introduces the design and analysis of algorithms, the management of information, and the programming mechanisms and methodologies required in implementations.

Introduction to numerical computation. The emphasis is on practical applications of the theory and concepts rather than formal rigour.

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CS 303 | CS 1303 | CS2303 Theory of Computation

Introduction to algorithm analysis and complexity theory. Correctness proofs for both recursive and iterative program constructions.

COMP – Analysis of Algorithms and Data Structures Fundamental algorithms for sorting, searching, storage management, graphs, databases and computational geometry. Topics discussed include iterative and recursive sorting algorithms; lists, stacks, queues, trees, and their application; abstract data types and their implementations.

NP- hardness and NP- completeness. Computer Science Introduction to Computability An introduction to abstract models of sequential computation, including finite automata, regular expressions, context-free grammars, and Turing machines. Strassen’s methodNP-completeness. UBC Notes – tons of math! Regular languages, finite automata, transition graphs Kleene’s theorem. Topics include elementary number theory gcd, lcm, Euclidean algorithm, congruences, Chinese remainder theorem and graph theory connectedness, complete, regular and bipartite graphs; trees and spanning trees, Eulerian and Hamiltonian graphs, planar graphs; vertex, face and edge colouring; chromatic polynomials.

External storage and input-output complexity. Intermediate Data Structures and Algorithms Formal abstract data types; tree representations and searching: