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Computer Science
·
Module 1
The Power of Finite Memory: Regular Languages
1
Understanding DFAs: Definition and Tracing
Define deterministic finite automata (DFA) formally and trace the computation of an input string.
2
NFA: Definition and Tracing Computation
Define nondeterministic finite automata (NFA) and trace the computation of an input string.
3
NFA to DFA Conversion using Subset Construction
Prove the equivalence of DFAs and NFAs by converting an NFA to an equivalent DFA using subset construction.
4
Introduction to Regular Expressions
Define regular expressions and write expressions for given language descriptions.
5
Regular Expressions and Finite Automata: Equivalence and Conversion
Establish the equivalence of regular expressions and finite automata by converting between them.
6
Proving Non-Regularity with the Pumping Lemma
Apply the pumping lemma for regular languages to prove that a given language is not regular.
7
Closure Properties of Regular Languages
Define and prove closure properties of regular languages (union, concatenation, Kleene star, intersection, complement).
8
Regular Expressions and Finite Automata in Practical Applications
Explain how regular expressions and finite automata are applied in lexical analysis, text search, and input validation.
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