Course Content
Introduction of Formal Language and Automata Theory:- Unit:- 1
Formal Language and Automata Theory is a branch of theoretical computer science that studies the abstract structures and models of computation. It focuses on formal languages, which are sets of strings defined by specific rules, and automata, which are abstract machines used to recognize and process these languages. The theory provides a foundation for understanding how computational systems work and aids in designing and analyzing algorithms and programming languages.
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Alphabet, languages and grammars
05:08 -
Productions
10:42 -
Derivation
06:22 -
Chomsky hierarchy of languages
12:46
Regular languages and finite Automata::- Unit:- 1
Regular Languages: Regular languages are a class of formal languages that can be expressed using regular expressions and recognized by finite automata. They are characterized by their ability to be described with a finite set of states and transitions, making them a subset of context-free languages.
Finite Automata: Finite automata are computational models with a finite number of states used to recognize regular languages. They consist of a set of states, a start state, transition functions, and accept/reject criteria to determine if a given input string belongs to the language.
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Regular Expressions
09:59 -
Regular Languages
06:37 -
Deterministic finite automata (DFA)
13:14 -
Equivalence with Regular Expressions
04:17 -
Non Deterministic Finite Automata (NFA)
09:01 -
Equivalence with NDFA
12:23 -
Regular Grammars
19:49 -
Equivalence with Finite Automata
11:05 -
Properties of Regular Languages
09:03 -
Pumping lemma for Regular Languages
12:00 -
Minimization of Finite Automata.
17:36
Context-Free Languages and Pushdown Automata:- Unit:- 2
Context-Free Languages (CFLs):
Context-Free Languages are a class of formal languages that can be generated by context-free grammars, where each production rule has a single non-terminal on the left-hand side. These languages are powerful enough to describe many programming language constructs, such as balanced parentheses and nested structures.
Pushdown Automata (PDA):
Pushdown Automata are computational models that extend finite automata by incorporating a stack. PDAs are used to recognize context-free languages, making them capable of handling nested structures and matching patterns, such as those found in context-free grammars.
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Context-free grammars (CFG) and languages (CFL)
07:52 -
Chomsky and Greibach normal forms
06:33 -
Non Deterministic Pushdown Automata (PDA)
10:59 -
Equivalence with CFG
22:49 -
Parse Trees
06:33 -
Ambiguity in CFG
06:38 -
Pumping lemma for Context Free Languages
08:06 -
Deterministic Pushdown Automata
09:24 -
Closure Properties of CFLs
07:32
Context sensitive languages:- Unit:- 3
Context-sensitive languages are a class of formal languages where the production rules in their grammars are such that each rule can only replace a string with another string of equal or greater length. These languages are more expressive than context-free languages and can describe certain patterns and constraints that context-free grammars cannot.
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Context-sensitive grammars (CSG) and languages
06:36 -
Linear Bounded Automata
06:40 -
Equivalence with CSG
06:39
Turing machines:- Unit:- 3
A Turing machine in Formal Language and Automata Theory (FLAT) is an abstract computational model that consists of an infinite tape, a tape head that reads and writes symbols, and a finite set of states. It is used to simulate any algorithm's logic, serving as a fundamental model for computation, capable of recognizing any language that can be described by a formal grammar.
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The basic model for Turing machines (TM)
09:26 -
Turing-recognizable (recursively enumerable) and Turing-decidable (recursive) languages
08:47 -
Closure properties Turing machines
32:24 -
Variants of Turing machines
11:07 -
Nondeterministic TMs
15:49 -
Equivalence with Deterministic TMs
10:21 -
Unrestricted Grammars
11:49 -
Equivalence with Turing machines
21:08 -
TMs as Enumerators.
02:21
Undecidability:- Unit:- 4
In formal language theory, undecidability refers to the property of a decision problem where no algorithm can determine the solution for all possible inputs. Specifically, it means that there is no algorithm that can decide, in a finite amount of time, whether a given input string belongs to a specific language or whether a given computational problem has a solution.
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Church-Turing Thesis
09:57 -
Universal Turing Machine
05:39 -
The universal and Diagonalization languages
11:30 -
Reduction between languages and Rice’s theorem
16:52 -
Undecidable problems about languages
04:53
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