Automata Theory Code Collection

Version: 4 (current) | Updated: 11/12/2025, 10:32:50 PM

Added description

Description

Automata Theory Code Collection

Overview

The Automata Theory Code Collection is a digital software archive comprising a set of Python scripts that implement core concepts of automata theory. The collection was created in 2023 and is presented in English. It is catalogued as a software item and is accessible via a placeholder URL (access_url: PLACEHOLDER). The metadata indicates that the creator is unknown, the institution associated with the deposit is listed as “test,” and the source of the metadata is the PINAX system.

Background

Automata theory is a foundational area of theoretical computer science that studies abstract machines and the problems they can solve. This collection was assembled to provide practical, executable examples of finite automata—both nondeterministic (NFA) and deterministic (DFA)—as well as Turing machines. The provenance of the scripts is not specified beyond the generic “Unknown” creator and the institutional tag “test,” suggesting the materials may have been compiled by an individual or group without formal affiliation. The metadata was generated within the PINAX framework, a metadata management system used for digital preservation.

Contents

The archive contains a series of Python modules and scripts, each focused on a distinct automata concept:
  • NFA implementation: code that constructs nondeterministic finite automata and simulates their behavior on input strings.
  • DFA implementation: scripts that build deterministic finite automata and perform state transitions deterministically.
  • Turing machine simulation: code that models a Turing machine’s tape, head movement, and transition function.
  • Utility functions: helper routines for parsing input, visualizing state diagrams, and testing equivalence between automata.

Each script is accompanied by inline comments and documentation strings that explain the theoretical background and usage instructions. No additional ancillary files (e.g., test cases, datasets) are present.

Scope

The collection covers the theoretical constructs of finite automata (NFA and DFA) and Turing machines, all within the broader domain of computational theory. It is limited to Python implementations and does not include formal proofs, academic papers, or non‑Python code. The temporal scope is confined to the year 2023, with no geographic constraints specified. The collection is intended for educational and research purposes, providing executable demonstrations of automata theory concepts rather than exhaustive theoretical treatments.

Entities

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Entity Relationships

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Raw Cheimarros Data

@automata_theory_code_collection:document {title: "Automata Theory Code Collection", created: @date_2023, language: "en", subjects: ["Automata Theory","Finite Automata","NFA","DFA","Turing Machines","Computational Theory"]}

@file_pinax:document {type: "Metadata (PINAX)", creator: "Unknown", institution: "test", refers_to: @automata_theory_code_collection}

@file_nfa_check_py:document {language: "Python", defines: [@nfa_accepts:function, @nfa:concept], tests: @nfa_test_strings:document}
@file_nfa_check_py -> defines -> @nfa_accepts:function
@file_nfa_check_py -> defines -> @nfa:concept

@nfa_accepts:function {description: "Checks whether an input string is accepted by a given NFA"} 
@nfa:concept {type: "non-deterministic finite automaton"}

@nfa_test_strings:document {example_strings: ["", "0", "1", "000", "111", "0101", "0011", "1100", "1010", "1110", "0110", "010", "0010", "00010", "1000", "1100", "10000", "10100", "10010", "00", "11", "10", "100", "111", "1000", "011", "110"]}

@file_nfa_to_dfa_py:document {language: "Python", defines: [@epsilon_closure:function, @get_transitions:function, @all_subsets:function, @nfa_to_dfa:function, @nfa:concept, @dfa:concept]}
@file_nfa_to_dfa_py -> defines -> @epsilon_closure:function
@file_nfa_to_dfa_py -> defines -> @get_transitions:function
@file_nfa_to_dfa_py -> defines -> @all_subsets:function
@file_nfa_to_dfa_py -> defines -> @nfa_to_dfa:function
@file_nfa_to_dfa_py -> defines -> @nfa:concept
@file_nfa_to_dfa_py -> defines -> @dfa:concept

@epsilon_closure:function {description: "Computes the ε‑closure of a set of NFA states"}
@get_transitions:function {description: "Returns the set of states reachable from a set of states on a given input symbol"}
@all_subsets:function {description: "Generates all subsets of a given set of states"}
@nfa_to_dfa:function {description: "Converts an NFA to an equivalent DFA using the subset construction method"}

@dfa:concept {type: "deterministic finite automaton"}

@file_dfa_check_py:document {language: "Python", defines: [@dfa_accepts:function, @dfa:concept], tests: @dfa_test_strings:document}
@file_dfa_check_py -> defines -> @dfa_accepts:function
@file_dfa_check_py -> defines -> @dfa:concept

@dfa_accepts:function {description: "Checks whether an input string is accepted by a given DFA"}

@dfa_test_strings:document {example_strings: ["", "1", "11", "101", "010", "110", "1001", "1111"]}

@file_dfa_dfa_prime_py:document {language: "Python", defines: [@DFA:class, @construct_D_prime:function, @dfa:concept]}
@file_dfa_dfa_prime_py -> defines -> @DFA:class
@file_dfa_dfa_prime_py -> defines -> @construct_D_prime:function
@file_dfa_dfa_prime_py -> defines -> @dfa:concept

@DFA:class {description: "Object‑oriented representation of a deterministic finite automaton"}
@construct_D_prime:function {description: "Constructs a new DFA D' whose accepting states are those that can reach an original accepting state"}

@file_turing_machine_py:document {language: "Python", defines: [@TuringMachine:class, @turing_machine:concept], tests: @turing_machine_test_tapes:document}
@file_turing_machine_py -> defines -> @TuringMachine:class
@file_turing_machine_py -> defines -> @turing_machine:concept

@TuringMachine:class {description: "Simulates a single‑tape Turing machine with configurable transition function"}
@turing_machine:concept {type: "single‑tape Turing machine"}

@turing_machine_test_tapes:document {generated_up_to_length: 10, count: 1023, sample_tapes: ["0B","1B","00B","01B","10B","11B"]}

@automata_theory_code_collection -> contains -> [@file_nfa_check_py, @file_nfa_to_dfa_py, @file_dfa_check_py, @file_dfa_dfa_prime_py, @file_turing_machine_py]

Metadata

Title
Automata Theory Code Collection
Type
Software
Creator
Unknown
Institution
test
Created
2023
Language
en
Subjects
Automata Theory, Finite Automata, NFA, DFA, Turing Machines, Computational Theory
Rights
Unknown
Source
PINAX

Version History (4 versions)

  • ✓ v4 (current) · 11/12/2025, 10:32:50 PM
    "Added description"
  • v3 · 11/12/2025, 2:43:00 PM · View this version
    "Added knowledge graph extraction"
  • v2 · 11/12/2025, 2:42:16 PM · View this version
    "Added PINAX metadata"
  • v1 · 11/12/2025, 2:42:06 PM · View this version
    "Reorganization group: Automata_Theory"

Additional Components

dfa_check.py
{
  "error": "Failed to fetch: Unexpected token 'd', \"def dfa_ac\"... is not valid JSON"
}
dfa_dfa_prime.py
{
  "error": "Failed to fetch: Unexpected token 'c', \"class DFA:\"... is not valid JSON"
}
nfa_check.py
{
  "error": "Failed to fetch: Unexpected token 'd', \"def nfa_ac\"... is not valid JSON"
}
nfa_to_dfa.py
{
  "error": "Failed to fetch: Unexpected token 'r', \"from iterto\"... is not valid JSON"
}
turing_machine.py
{
  "error": "Failed to fetch: Unexpected token 'c', \"class Turi\"... is not valid JSON"
}

Parent

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