nfa

I am doing an assignment for simulate a nondeterministic finite automaton, just as I explain in this post . I have this input read from the file tarea4.in : 1 6 8 0 2 2 5 0 0 a 0 1 a 1 1 b 1 2 c 1 3 c 3 4 d 4 4 d 4 5 d 5 aaabcccc aabbbbcdc abbcdddcc acdddddd abc The first line of input is an integer T, represented the number of cases to evaluate the program. Each test case starts with 4 integers, the first is the number of state for the automaton, next is the number of transitions of the automaton, the third number is the initial state, and then the number of final states. then come the final

Does anyone know of any good NFA and DFA implementation in C#, possibly implementing as well conversions between both? What I would like would be to be able to construct a NFA and then convert it automatically to a DFA, but without having to write my own code which would take a very long time. There is this Python code which perhaps I could use and integrate with C# using IronPython, but Python is slow. Take a look at my series of posts about this subject: Regular Expression Engine in C# (the Story) Regex engine in C# - the Regex Parser Regex engine in C# - the NFA Regex engine in C# - the DFA

I'm having issues 'describing each step' when creating an NFA from a regular expression. The question is as follows: Convert the following regular expression to a non-deterministic finite-state automaton (NFA), clearly describing the steps of the algorithm that you use: (b|a)*b(a|b) I've made a simple 3-state machine but it's very much from intuition. This is a question from a past exam written by my lecturer, who also wrote the following explanation of Thompson's algorithm: http://www.cs.may.ie/staff/jpower/Courses/Previous/parsing/node5.html Can anyone clear up how to 'describe each step

How does one implement a dfa or an nfa for that matter in Python code? What are some good ways to do it in python? And are they ever used in real world projects? A straightforward way to represent a DFA is as a dictionary of dictionaries. For each state create a dictionary which is keyed by the letters of the alphabet and then a global dictionary which is keyed by the states. For example, the following DFA from the Wikipedia article on DFAs can be represented by a dictionary like this: dfa = {0:{'0':0, '1':1}, 1:{'0':2, '1':0}, 2:{'0':1, '1':2}} To "run" a dfa against an input string drawn

Using pumping lemma, we can easily prove that the language L1 = {WcW^R|W ∈ {a,b}*} is not a regular language . (the alphabet is {a,b,c}; W^R represents the reverse string W) However, If we replace character c with "x"(x ∈ {a,b}+) , say, L2 = {WxW^R| x, W ∈ {a,b}^+} , then L2 is a regular language . Could you give me some ideas? Grijesh Chauhan If we replace character c with x where (x ∈ {a,b} + ), say, L2 = {WXW R | x, W ∈ {a,b} + }, then L2 is a regular language. Yes, L2 is Regular Language :). You can write regular expression for L2 too. Language L2 = {WXW R | x, W ∈ {a,b} + } means: string

I am looking for a non-technical explanation of the difference between DFA vs NFA engines, based on their capabilities and limitations. David Thornley Deterministic Finite Automatons (DFAs) and Nondeterministic Finite Automatons (NFAs) have exactly the same capabilities and limitations. The only difference is notational convenience. A finite automaton is a processor that has states and reads input, each input character potentially setting it into another state. For example, a state might be "just read two Cs in a row" or "am starting a word". These are usually used for quick scans of text to