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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Discrete structures as they apply to computer science, algorithm analysis and design. CS Logic and Computation Propositional and predicate logic. Interpretations, validity, and satisfiability. Covers advanced techniques for analyzing recursive algorithms, examines major algorithm-design approaches including greedy, divide and conquer, dynamic programming, and graph-based approaches.
Optional topics include set theory and induction using the formal logical language of the first part of the course.
Unified approaches to programming and theoretical problems. String and graph problems, such as string matching and shortest path. Properties of the integers.
Considers randomized algorithms and introduces complexity theory, including NP-completeness.
This page was last edited on 25 Januaryat CMPT Design and Cs1303-thoery of Computing Algorithms Models of computation, methods of algorithm design; complexity of algorithms; algorithms on graphs, NP-completeness, approximation algorithms, selected topics Choice: CS Elementary Algorithm Design and Data Abstraction This course builds on the techniques and patterns learned in CS while making the transition to use of an imperative language.
P and NP classes.
CR: Survey of theory requirements in other Canadian Honours programs
Computational complexity of problems: Topics covered include graph theory, trees, inclusion-exclusion, generating functions, recurrence computatioon, and optimization and matching. Theory of Computation Finite Automata, regular cs1303-tjeory and languages; properties of regular languages; context-free grammars and languages; pushdown automata; properties of context-free languages. Random access machine model. CS Discrete Structures I Introduces topics in discrete mathematics important in Computer Science, including propositional logic, predicate logic, proofs, sigma notation, mathematical induction, elementary set theory and asymptotic analysis.
Worst-case, average-case, and best-case analysis.
CS | CS | CS Theory of Computation |
CSC Foundations of Computer Science A survey of formal models and results that form the theoretical foundations of computer science; typical topics include finite automata, Turing machines, undecidable problems, context free languages and computational complexity. What are the components of Finite automaton model? Properties of integers and basic cryptographical applications.
What is a regular expression? Views Read View source View history. CSI Discrete Structures 3,1. There is a unique transition on each input symbol. Home You are here: S Theory of Computation Models of sequential and parallel computation, automata theory, formal languages, the Chomsky hierarchy, decidability and computability, sequential and parallel complexity theory.
Their advising material says those who want to do an honours degree but don’t have any specialty in mind should take this option. This course includes recursion, abstract data types and selected topics exploring some of the breadth of computer science. What are the applications of automata theory?
Correctness proofs for both recursive and iterative program constructions. Specific topics include priority queues, sorting, dictionaries, data structures for text processing.
Choice of one of three: CS Data Structures and Data Management Introduction to widely used and effective methods of data organization, focusing on data structures, their algorithms, and the performance of these algorithms. Computer Science Introduction to Computability An introduction to abstract models of sequential computation, including finite automata, regular expressions, context-free grammars, and Turing machines.
Topics include linear lists, stacks, queues, linked structures, trees, binary trees; sorting techniques, including heap sort, quick sort, merge sort, shell sort; searching techniques including binary search, binary search trees, red-black trees, hashing.
Efficient implementation of lists, sets, dictionaries, priority queues, trees, graphs, and networks using arrays, hash tables, heaps, and hierarchical linked structures. A “theory” course is any course, taught by any department, that is mainly: The emphasis is on using these structures and assessing the relative effectiveness of alternative implementations. P 1 is true. Simple methods of complexity analysis.
The components of FA model are Input tape, Read control and finite control.
CS Data Structures Covers mathematical and experimental techniques for algorithm analysis and cs1303-thelry application to the major techniques for representing and manipulating data structures in main memory. Introduction to numerical computation. Topics discussed include iterative and recursive sorting algorithms; lists, stacks, queues, trees, and their application; abstract data types and their implementations.
Elementary searching and sorting. Applications to program specification and verification.