
- 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
Pushdown Automata Graphical Notation
In context-free grammars, we have understood about a machine called Pushdown Automaton. A Pushdown Automaton is a powerful machine than a Finite Automaton which accepts context free grammars.
With Pushdown Automata, we can handle more complex language patterns. In this chapter, we will have a closer look at the concept of Pushdown Automata along with their graphical notation to have a better understanding of PDA in action.
Components of a Pushdown Automata
A PDA has several parts working together:
- An input tape − This holds the string we want to check.
- A reading head − It reads symbols from the input tape.
- A finite control − This is like the brain of the PDA.
- A stack − This is a special storage area that helps the PDA remember things.
Mathematical Representation of Pushdown Automata
We can describe a PDA using a set of seven things. We call this a 7-tuple: (Q, Σ, Γ, δ, q0, z0, F)
- Q − All the states the PDA can be in
- Σ − The input alphabet (symbols it can read)
- Γ − The stack alphabet (symbols it can put on the stack)
- δ − Rules for moving between states
- q0 − The starting state
- z0 − The symbol at the bottom of the stack
- F − The final or accepting states
Graphical Notation for Pushdown Automata
Now, let's talk about how we can draw a Pushdown Automata. It's often easier to understand when we can see it!
Basic Elements
- States − We draw these as circles.
- Start State − This is a circle with an arrow pointing to it.
- Final State − We use a double circle for this.
- Transitions − These are arrows between states.
Transition Labels
The labels on the arrows are very important. They tell us three things:
- The input symbol being read
- The symbol at the top of the stack before the move
- What happens to the stack after the move
We write these as: input symbol, stack top / new stack top
Let us see the idea of drawing PDA with some examples.
Example 1: PDA for Equal 'a's and 'b's
We want to build a PDA for the language L = (a, b)* where the number of 'a's equals the number of 'b's.
PDA Design
Here's how our PDA will work:
- Start with an empty stack (just z0 at the bottom).
- When we see an 'a', push z1 onto the stack.
- When we see a 'b', push z2 onto the stack.
- If we see 'b' after 'a', pop z1 from the stack.
- If we see 'a' after 'b', pop z2 from the stack.
- If we see 'a' after 'a', push another z1.
- If we see 'b' after 'b', push another z2.

How to Read the Transitions?
- (a, z0/z1z0): Read 'a', replace z0 with z1z0
- (b, z0/z2z0): Read 'b', replace z0 with z2z0
- (a, z1/z1z1): Read 'a', push another z1
- (b, z2/z2z2): Read 'b', push another z2
- (b, z1/λ): Read 'b', pop z1 (λ means remove)
- (a, z2/λ): Read 'a', pop z2
- (λ, z0/z0): Empty input, z0 on stack, go to final state
Example 2: Pushdown Automata for WCWR
Let's look at another example. This time, we'll create a PDA for the language L = {WCWR}, where W is any string of 'a's and 'b's, and WR is W reversed.
Pushdown Automata Design
Here's how our PDA will work:
- Start with z0 at the bottom of the stack.
- For the first part (W), push z1 for 'a' and z2 for 'b'.
- When we see 'C', don't change the stack, just move to the next state.
- For the second part (WR), pop z1 for 'a' and z2 for 'b'.
- If we end with just z0 on the stack, accept the string.

How to Read the Transitions?
- (a, z0/z1z0): Start of W, read 'a', push z1
- (b, z0/z2z0): Start of W, read 'b', push z2
- (a, z1/z1z1), (b, z2/z2z2): Continue W, push corresponding symbol
- (b, z1/z2z1), (a, z2/z1z2): Handle alternating 'a' and 'b' in W
- (C, z1/z1), (C, z2/z2): Read 'C', don't change stack
- (a, z1/λ), (b, z2/λ): For WR, pop matching symbol
- (λ, z0/z0): Empty input, z0 on stack, go to final state
Conclusion
Graphical notation for PDAs helps us visualize how these machines work. It shows us the states, the transitions between them, and how the stack changes. This makes it easier to understand and design PDAs for different languages.
In this chapter, we explained the graphical notations and presented two examples with steps and suitable state transition diagrams for a clear understanding.