
- Automata Theory - Applications
- Automata Terminology
- Basics of String in Automata
- Set Theory for Automata
- Finite Sets and Infinite Sets
- Algebraic Operations on Sets
- Relations Sets in Automata Theory
- Graph and Tree in Automata Theory
- Transition Table in Automata
- What is Queue Automata?
- Compound Finite Automata
- Complementation Process in DFA
- Closure Properties in Automata
- Concatenation Process in DFA
- Language and Grammars
- Language and Grammar
- Grammars in Theory of Computation
- Language Generated by a Grammar
- Chomsky Classification of Grammars
- Context-Sensitive Languages
- Finite Automata
- What is Finite Automata?
- Finite Automata Types
- Applications of Finite Automata
- Limitations of Finite Automata
- Two-way Deterministic Finite Automata
- Deterministic Finite Automaton (DFA)
- Non-deterministic Finite Automaton (NFA)
- NDFA to DFA Conversion
- Equivalence of NFA and DFA
- Dead State in Finite Automata
- Minimization of DFA
- Automata Moore Machine
- Automata Mealy Machine
- Moore vs Mealy Machines
- Moore to Mealy Machine
- Mealy to Moore Machine
- Myhill–Nerode Theorem
- Mealy Machine for 1’s Complement
- Finite Automata Exercises
- Complement of DFA
- Regular Expressions
- Regular Expression in Automata
- Regular Expression Identities
- Applications of Regular Expression
- Regular Expressions vs Regular Grammar
- Kleene Closure in Automata
- Arden’s Theorem in Automata
- Convert Regular Expression to Finite Automata
- Conversion of Regular Expression to DFA
- Equivalence of Two Finite Automata
- Equivalence of Two Regular Expressions
- Convert Regular Expression to Regular Grammar
- Convert Regular Grammar to Finite Automata
- Pumping Lemma in Theory of Computation
- Pumping Lemma for Regular Grammar
- Pumping Lemma for Regular Expression
- Pumping Lemma for Regular Languages
- Applications of Pumping Lemma
- Closure Properties of Regular Set
- Closure Properties of Regular Language
- Decision Problems for Regular Languages
- Decision Problems for Automata and Grammars
- Conversion of Epsilon-NFA to DFA
- Regular Sets in Theory of Computation
- Context-Free Grammars
- Context-Free Grammars (CFG)
- Derivation Tree
- Parse Tree
- Ambiguity in Context-Free Grammar
- CFG vs Regular Grammar
- Applications of Context-Free Grammar
- Left Recursion and Left Factoring
- Closure Properties of Context Free Languages
- Simplifying Context Free Grammars
- Removal of Useless Symbols in CFG
- Removal Unit Production in CFG
- Removal of Null Productions in CFG
- Linear Grammar
- Chomsky Normal Form (CNF)
- Greibach Normal Form (GNF)
- Pumping Lemma for Context-Free Grammars
- Decision Problems of CFG
- Pushdown Automata
- Pushdown Automata (PDA)
- Pushdown Automata Acceptance
- Deterministic Pushdown Automata
- Non-deterministic Pushdown Automata
- Construction of PDA from CFG
- CFG Equivalent to PDA Conversion
- Pushdown Automata Graphical Notation
- Pushdown Automata and Parsing
- Two-stack Pushdown Automata
- Turing Machines
- Basics of Turing Machine (TM)
- Representation of Turing Machine
- Examples of Turing Machine
- Turing Machine Accepted Languages
- Variations of Turing Machine
- Multi-tape Turing Machine
- Multi-head Turing Machine
- Multitrack Turing Machine
- Non-Deterministic Turing Machine
- Semi-Infinite Tape Turing Machine
- K-dimensional Turing Machine
- Enumerator Turing Machine
- Universal Turing Machine
- Restricted Turing Machine
- Convert Regular Expression to Turing Machine
- Two-stack PDA and Turing Machine
- Turing Machine as Integer Function
- Post–Turing Machine
- Turing Machine for Addition
- Turing Machine for Copying Data
- Turing Machine as Comparator
- Turing Machine for Multiplication
- Turing Machine for Subtraction
- Modifications to Standard Turing Machine
- Linear-Bounded Automata (LBA)
- Church's Thesis for Turing Machine
- Recursively Enumerable Language
- Computability & Undecidability
- Turing Language Decidability
- Undecidable Languages
- Turing Machine and Grammar
- Kuroda Normal Form
- Converting Grammar to Kuroda Normal Form
- Decidability
- Undecidability
- Reducibility
- Halting Problem
- Turing Machine Halting Problem
- Rice's Theorem in Theory of Computation
- Post’s Correspondence Problem (PCP)
- Types of Functions
- Recursive Functions
- Injective Functions
- Surjective Function
- Bijective Function
- Partial Recursive Function
- Total Recursive Function
- Primitive Recursive Function
- μ Recursive Function
- Ackermann’s Function
- Russell’s Paradox
- Gödel Numbering
- Recursive Enumerations
- Kleene's Theorem
- Kleene's Recursion Theorem
- Advanced Concepts
- Matrix Grammars
- Probabilistic Finite Automata
- Cellular Automata
- Reduction of CFG
- Reduction Theorem
- Regular expression to ∈-NFA
- Quotient Operation
- Parikh’s Theorem
- Ladner’s Theorem
Kleene's Theorem in Automata Theory
Kleene's Theorem states the equivalence of the following three statements −
- A language accepted by Finite Automata can also be accepted by a Transition graph.
- A language accepted by a Transition graph can also be accepted by Regular Expression.
- A language accepted by Regular Expression can also be accepted by finite Automata.
Kleene's Theorem Proof Part-1
A language accepted by Finite Automata can also be accepted by a Transition graph.
Consider an example Let L = aba over an alphabet {a, b}

Third Part of Kleene's Theorem
A language accepted by Regular Expression can also be accepted by finite Automata.
Theorem
Any language that can be defined with RE can be accepted by some Finite State Machine (FSM) is also regular.
Proof
The proof is by construction.
For a given RE α, we can construct a FSM M such that
$$\mathrm{L (\alpha) \:=\: L (M)}$$
If α is any c € Σ, we can construct a simple FSM as follows −

If α is φ, we construct simple FSM as follows −
If α is €, we construct simple FSM as −
Let us construct FSMs to accept language that are defined by regular expression that exploits the operations of concatenation, union and Kleene star.
Step 1 − Let β and γ be RE that defined languages over the alphabet Σ
If L(β) is regular, then it is accepted by some FSM
$$\mathrm{M1 \:=\: (Q1,\: \Sigma,\: \delta 1,\: q1,\: F1)}$$
Let L(γ) is regular, then it is accepted by some FSM
$$\mathrm{M2 \:=\: (Q2,\: \Sigma,\: \delta 2,\: q2,\: F2)}$$
Step 2 − If RE α = β ∪ γ and if both L(β) and L(γ) are regular,
Then we construct M3 =( Q3, Σ, δ3, q3, F3), such that
$$\mathrm{L(M3) \:=\: L(\alpha) \:=\: L(\beta) \: \cup \: L(\gamma)}$$
Step 3 − Let P accept L = {a} and Q accepts L = {b}, then R can be represented as a combination of P and Q by using the provided operations as −
$$\mathrm{R \:=\: P \:+\: Q}$$
Transition Diagram
The transition diagram for the same is given below −

We observe the following in the transition diagram −
- In case of union operation we can have a new start state. From there, a null transition proceeds to the starting state of both the Finite State Machines.
- The final states of both the Finite Automata are converted to intermediate states. The final state is unified into one which can be traversed by null transitions.