Is the DFA Solution for Regular Expressions Accurate?

In summary, a DFA (Deterministic Finite Automaton) for regular expression is a finite state machine that recognizes strings matching a given regular expression by reading input symbols and transitioning between states. The main difference between a DFA and an NFA (Non-deterministic Finite Automaton) is that a DFA has one unique transition for each input symbol and state combination, while an NFA can have multiple transitions. To construct a DFA for a regular expression, the regular expression must first be translated into an NFA and then converted using the subset construction algorithm. DFAs can recognize all regular languages, but some may require a large number of states. The main advantages of using a DFA for regular expression are its efficiency, determinism, and predictability.
  • #1
shivajikobardan
674
54
Homework Statement
NDFA for (ba)* U (bab)*. Convert this to DFA.
Relevant Equations
none
1650118147393.png


but the solution site says otherwise-:
https://cyberzhg.github.io/toolbox/nfa2dfa

1650118207232.png

I feel correct mine also, but not sure. Check it please.
 
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  • #2
Your DFA accepts is babba. But should it?
 

Related to Is the DFA Solution for Regular Expressions Accurate?

What is DFA for regular expression?

DFA stands for Deterministic Finite Automaton. It is a finite state machine that recognizes patterns in strings of characters, also known as regular expressions. It is commonly used in computer science and programming to validate input and search for specific patterns in text.

How does DFA for regular expression work?

DFA works by reading a string of characters and transitioning between states based on the current input. It starts at the initial state and follows a series of transitions until it reaches an accepting state. If the input string matches the pattern described by the DFA, it will end in an accepting state, indicating a successful match.

What are the advantages of using DFA for regular expression?

DFA is a fast and efficient way to search for patterns in text. It has a linear time complexity, meaning the time it takes to process an input is directly proportional to the length of the input. It also has a small memory footprint, making it suitable for use in memory-constrained environments.

What are the limitations of DFA for regular expression?

DFA can only recognize regular languages, which are a subset of all possible languages. This means that it cannot handle more complex patterns such as nested parentheses or matching an equal number of opening and closing brackets. Additionally, DFA can become very large and complex for more complex regular expressions, making it difficult to manage and maintain.

How is DFA for regular expression different from NFA?

NFA stands for Nondeterministic Finite Automaton. Unlike DFA, NFA can have multiple possible transitions for a given input, making it more flexible but also more complex. DFA always has a unique transition for each input, making it deterministic. NFA is often converted to DFA for efficient pattern matching, but it can also recognize some non-regular languages that DFA cannot.

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