
- 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
Quotient Operation in Automata Theory
In this chapter, we will see the concept of the quotient operation in automata theory. We will see how regular languages are closed under quotient operations, then explain the concept with easy understandable form and provide detailed examples for them.
Quotient Operation
We know the term "quotient," we usually think of division, as learned in mathematics. The quotient is the result of dividing one number by another. However, in the Theory of Computation, the quotient operation is not exactly the same as in mathematics, although it shares a similar conceptual foundation. It is important to note that the quotient operation in TOC is not about division for numbers, but rather about manipulating strings in languages.
Understanding Quotient in Theory of Computation
In the context of automata, the quotient operation can be seen as a way to "cut" parts of strings within languages. There are two types of quotient operations: the left quotient and the right quotient.
- Left Quotient − Also referred to as "cutting the prefix."
- Right Quotient − Also referred to as "cutting the suffix."
Let us see these operations more formally.
Formal Definition of Quotient Operation
The quotient of two languages, say L1 and L2, denoted by L1 / L2, is defined as follows −
$$\mathrm{\frac{L_1}{L_2} \:=\: \{ x\: \mid \:\text{ for some } \:y\: \in\: L_2,\: \,\: xy\: \in \:L_1 \}}$$
Here, L1 and L2 are two languages over the same input symbol set. This input symbol set could be {0, 1}, {a, b}, or any other set of symbols. The languages L1 and L2 can be either finite or infinite, but they must be defined over the same set of input symbols.
How the Quotient is Determined?
The quotient operation results in a new language by "cutting" or removing part of the string, depending on whether we are performing a left quotient or a right quotient.
- Right Quotient − If we take a right quotient of L1 by L2, we match the right part of the string with L2. What is remaining after this match is the quotient.
- Left Quotient − If we take a left quotient of L1 by L2, we match the left part of the string with L2. The remaining part of the string is the quotient.
Examples of Quotient Operation
Now, let's take a look at some examples of Quotient Operation.
Example of Left Quotient
Let us see two languages −
$$\mathrm{L_{1} \:=\: \{10,\: 100,\: 1010,\: 101110\}}$$
$$\mathrm{L_{2} \:=\: \{10\}}$$
Both languages are defined over the input symbol set {0, 1}.
To find the left quotient, we compare each string in L1 with the string in L2, focusing on the left side.
First string in L1: 10
- L2 = 10
- We match 10 from the left of 10, leaving us with null
- Output:
Second string in L1: 100
- L2 = 10
- We match 10 from the left of 100, leaving us with "0."
- Output: 0
Third string in L1: 1010
- L2 = 10
- We match 10 from the left of 1010, leaving us with "10."
- Output: 10
Fourth string in L1: 101110
- L2 = 10
- We match 10 from the left of 101110, leaving us with "1110."
- Output: 1110
So, the left quotient L1 / L2 results in the language: { ∈, 0, 10, 1110}.
Example of Right Quotient
Now let us calculate the right quotient of the same languages L1 and L2.
First string in L1: 10
- L2 = 10
- We match 10 from the right of 10, leaving us with nothing
- Output: ∈
Second string in L1: 100
- L2 = 10
- There is no match with 10 on the right side, so the output is "Epsilon" (the empty string).
- Output: ∈
Third string in L1: 1010
- L2 = 10
- We match 10 from the right of 1010, leaving us with "10."
- Output: 10
Fourth string in L1: 101110
- L2 = 10
- We match 10 from the right of 101110, leaving us with "1011."
- Output: 1011
So, the right quotient L1 / L2 results in the language: {∈, ∈, 10, 1011}.
Example of Working with Regular Expressions
Let us explore an example involving regular expressions.
$$\mathrm{L_{1} \:=\: a^{*}b}$$
$$\mathrm{L_{2} \:=\: ab^{*}}$$
Here, we open L1 by substituting different values for the * in a −
$$\mathrm{a^{0}b \:\rightarrow\: b}$$
$$\mathrm{a^{1}b \:\rightarrow\: ab}$$
$$\mathrm{a^{2}b \:\rightarrow\: aab}$$
$$\mathrm{a^{3}b \:\rightarrow\: aaab}$$
Here, we open L2 by substituting different values for the * in b −
$$\mathrm{ab^{0} \:\rightarrow\: b}$$
$$\mathrm{ab^{1} \:\rightarrow\: ab}$$
$$\mathrm{ab^{2} \:\rightarrow\: abb}$$
$$\mathrm{ab^{3} \:\rightarrow\: abbb}$$
Now, calculate the left quotient L1 / L2, we pick each of L2, and check to find quotient on each of L1.
Closure Property of Regular Languages under Quotient Operation
Now, let us discuss why regular languages are closed under quotient operations. Closure property means that performing a certain operation on regular languages results in another regular language.
Why Are Regular Languages Closed Under Quotient Operation?
Regular languages are closed under quotient because when we perform the quotient operation, we are essentially reducing or cutting parts of the strings in the language. We are not adding anything new; we are just cutting or trimming existing parts. This operation results in a language that still retains the structure of a regular language.
If L1 and L2 are regular languages, then their quotient, L1 / L2, is also a regular language.
Conclusion
In this chapter, we covered the concept of the quotient operation in automata theory. We discussed what quotient operation is, how it is defined in the regular languages and regular expressions, and how to calculate it using both left and right quotient methods.
We worked through detailed examples to understand the application of the quotient operation. Finally, we learned about the closure property of regular languages under the quotient operation, which ensures that regular languages remain regular even after such operations.