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What Is The Difference Between DFA And NFA?

Deterministic Finite Automata (DFA) and Nondeterministic Finite Automata (NFA) are two types of finite automata (also known as Finite State Machine). In the Theory of Computation, DFA and NFA are Finite Accepters but use different approaches to reach the final states. Before examining their differences, we must familiarise ourselves with finite automata and how they work.

What are Finite Automata?

Finite Automata (FA) are mathematical models used to represent and control the behaviour of systems with a finite number of states. They are essential in computer science and linguistics for modeling and analyzing various computational processes, particularly those involving pattern recognition, text processing, and control systems.

Automata are a type of abstract machine with a finite number of states. They transition from one state to the next based on input. Since a Finite Automaton has no temporary storage, it can only remember a limited amount of information, relying solely on its finite control, which consists of states and transitions.

Key Components of Finite Automata

States: A finite set of conditions or configurations the automaton can be in. One of these states is the initial state, where the automaton begins, and one or more may be accepting (or final) states, where the automaton successfully terminates.
Alphabet: A finite set of symbols or characters that the automaton reads as input.
Transitions: A set of rules that dictate how the automaton moves from one state to another based on the input symbol it reads. This is often represented as a transition table or state diagram.
Acceptance: A string is accepted by the automaton if, after reading the entire string, the automaton ends in an accepting state.

Representation of FA

FA = (Q, Ʃ, δ, q₀, F) is a five tuple notation

Where Q is the set of final states.
Ʃ is an input alphabet that contains a finite number of input symbols.
δ is the transition function defined over transitions of FA for state and input.
q₀is the initial state or start state of FA, q₀ ∈ Q
F is the set of final states of FA.
Finite automata are divided into two categories:

Deterministic Finite Automata (DFA)

A Deterministic Finite Automaton (DFA) is an abstract mathematical model used in both software and hardware to address specific computational challenges. It is a theoretical concept that operates based on deterministic rules.

In a DFA, for each state and every input symbol in the alphabet, there is exactly one possible state transition. This characteristic distinguishes it from other types of automata, making it a "deterministic finite-state machine" or "deterministic finite accepter."

A DFA processes both valid and invalid strings in a regular language, ensuring that all valid strings lead to a final state and all invalid strings result in a non-final state. Each input string produces a unique, predictable computation or run, enabling the DFA to be fully automated.

Specification of DFA

DFA = (Q, Ʃ, δ, q_o, F) is a five tuple automata.

where Q is the set of final states

Ʃ is an input alphabet containing a finite number of input symbols.
δ is a transition function defined over transitions of FA for state and input (δ: Q X Ʃ --> Q)
q_o is an initial state or start state of DFA (q_o ∈ Q).
F is the set of final states of DFA

Example: Construct a DFA which contains all binary strings, where each string contains 000, as a substring.

Non-Deterministic Finite Automata (NFA)

A Nondeterministic Finite Automaton (NFA) is a type of abstract machine used in computation that can exist in multiple states simultaneously. It allows for multiple possible transitions from one state to another based on the same input.

For every valid string, an NFA ensures at least one path from the initial state to a final state. Unlike a Deterministic Finite Automaton (DFA), an NFA does not require transitions for invalid combinations and may include empty string transitions, where the automaton can change states without consuming an input symbol. Although NFAs are generally less efficient in processing input strings than DFAs, every NFA can be converted into an equivalent DFA.

Specification of NFA

NFA = (Q, Ʃ, δ, q_o, F) is a five tuple notation

Where Q is set of finite states

Ʃ is a set of non-empty finite input symbol
δ is a transition function defined over transitions of NFA for state and input.(δ: Q X Ʃ --> 2^Q)
q_o is a start state of NFA (q_o ∈ Q).
F is the set of final states of NFA

Example: Construct an NFA for strings of length at most 2

Difference between DFA and NFA

Let's discuss the key difference between DFA and NFA:

Deterministic FInite Automata (DFA)	Nondeterministic Finite Automata (NFA)
Building a DFA is difficult.	An NFA is simple to construct.
In DFA, just a single state transition may be achieved for each symbolic representation of the alphabet.	The user does not require to provide any information about how various symbols influence the NFA.
In DFA, the next potential state is explicitly defined.	Every pair of input symbols and states in NFA might contain many possible states.
NFAs are the source of all DFAs.	All NFAs are not DFAs.
There is a need for more space allocation	There is less need for space requirement.
In DFA, the total time it takes to run any input string is less than it is in NFA.	In comparison to DFA, the total time required to run any input string in NFA is longer.
It doesn't know how to handle an empty string transition.	It is capable of handling empty string transitions.
Dead state may be required.	Dead state is not required.
Backtracking is permitted in DFA.	Backtracking is not permitted in the NFA.
DFA is best explained and comprehended as a single machine.	NFA is similar to a collection of small machines that are all working on the same problem at the same time.
The DFA transition function is δ: Q X Ʃ --> Q	The NFA transition function is δ: Q X Ʃ --> 2^Q
If the string's termination state isn't the acceptable state, DFAs will reject it.	NFA, on the other hand, rejects the string only if all of the NFA's branches are dead or refuse to accept it.

In other words, DFA (Deterministic Finite Automaton) has a single unique transition for each input symbol from every state, ensuring deterministic behavior. In contrast, NFA (Nondeterministic Finite Automaton) allows multiple transitions or none for an input symbol from any state, leading to nondeterminism. While both accept the same class of languages, NFAs can be more complex in construction.

Similarities between DFA and NFA

Both DFAs and NFAs accept Type-3 languages, also known as regular languages.
DFAs and NFAs are equivalent in power, meaning they can recognize the same set of languages.
Every DFA is a specific type of NFA, but not every NFA is a DFA.
The transition function for a DFA is defined as $\times \Sigma \rightarrow Q$ , whereas for an NFA, it is $\times \Sigma \rightarrow 2^Q$ .
Constructing an NFA is often simpler than constructing a DFA for many cases.
In an NFA, each input symbol can have zero or more transitions from any given state, whereas in a DFA, each input symbol has exactly one transition from each state.

Note

DFA = NFA = ∈-NFA

Each move of a deterministic finite automaton is determined uniquely by reading an input.

A non-deterministic finite automaton has a set of possible actions for each move.

All these three finite automata accept the same class of languages called regular languages.

Every DFA is also a special case of NFA

NFA can be converted to DFA using subset construction.

∈-NFA can be converted to NFA and also to DFA.

Types of Finite Automata

Finite automata with output

These automata generate output based on their state transitions while processing input strings. They are often used in applications requiring responses or outputs corresponding to inputs. The two types are:

Moore Machine

Produces output based on its current state.
The output is associated with states, meaning it only changes when entering a new state.

Mealy Machine

Produces output based on both its current state and the input symbol.
The output can change during transitions, providing a more immediate response to inputs.

Also Read: Difference Between Mealy And Moore Machine (Comparison Table)

Finite automata without output

These automata do not generate any output during their processing of input strings. Their primary function is to accept or reject strings based on defined state transitions. These are of two types:

Deterministic Finite Automata (DFA)

It's finite automata with deterministic behavior. In DFA, there is exactly one transition from any state of finite automata for each input symbol.
It accepts the string by halting at a final state, and it rejects it by halting at a non-final state.

Non-deterministic Finite Automata (NFA)

It is a finite automata that isn't deterministic. In NFA, there are zero or more transitions from any state of finite automata for each input symbol.
It accepts the string by halting in a final state, and it rejects the string by halting in a non-final state or in a dead configuration.

What is a ∈-NFA?

An ε-NFA is a type of Nondeterministic Finite Automaton that allows transitions without consuming any input symbol, known as epsilon (ε) transitions. This feature provides additional flexibility in state transitions, enabling the automaton to move from one state to another without reading an input symbol.

With this, we come to the end of this article. We hope you found it interesting. Now that we've understood the similarities and differences, we can conclude that their power is equivalent. Although the total time required to manage every input string in NFA is more than in DFA, In comparison to NFA, constructing a DFA is more complicated.

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Shreeya Thakur

Sr. Associate Content Writer at Unstop

I am a biotechnologist-turned-content writer and try to add an element of science in my writings wherever possible. Apart from writing, I like to cook, read and travel.