Repository Analysis

faker-ruby/faker

A library for generating fake data such as names, addresses, and phone numbers.

3.0 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of faker-ruby/faker, a Ruby project with 11,832 GitHub stars. SynthScan v2.0 examined 254,597 lines of code across 1136 source files, recording 762 pattern matches distributed across 6 syntactic categories. The overall adjusted score of 3.0 places this repository in the Likely human-written band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

3.0
Adjusted Score
3.0
Raw Score
100%
Time Factor
2026-07-12
Last Push
11.8K
Stars
Ruby
Language
254.6K
Lines of Code
1.1K
Files
762
Pattern Hits
2026-07-14
Scan Date
0.00
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 0MEDIUM 1LOW 761

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 762 distinct pattern matches across 6 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Over-Commented Block736 hits · 734 pts
SeverityFileLineSnippetContext
LOWCONTRIBUTING.md121 - Set as `next` for new methods or methods with new featuresCOMMENT
LOWtest/test_helper.rb21YAML::ENGINE.yamler = 'psych' if defined? YAML::ENGINECOMMENT
LOWlib/faker.rb81 def bothify(string)COMMENT
LOWlib/locales/en/bank.yml1# Most of the iban details and the idea were copied from: https://github.com/iulianu/iban-toolsCOMMENT
LOWlib/faker/music.rb21 # Faker::Music.key #=> "A#"COMMENT
LOWlib/faker/music.rb41 ##COMMENT
LOWlib/faker/music.rb61 NOTE_LETTERSCOMMENT
LOWlib/faker/music.rb81 #COMMENT
LOWlib/faker/music.rb101 #COMMENT
LOWlib/faker/music.rb121 endCOMMENT
LOWlib/faker/internet.rb21 class << selfCOMMENT
LOWlib/faker/internet.rb101 [Faker::Name.first_name, Faker::Name.last_name].map do |name|COMMENT
LOWlib/faker/internet.rb181 # Returns the domain nameCOMMENT
LOWlib/faker/internet.rb221 #COMMENT
LOWlib/faker/internet.rb261COMMENT
LOWlib/faker/internet.rb281 # @return [String]COMMENT
LOWlib/faker/internet.rb301 ##COMMENT
LOWlib/faker/internet.rb341 #COMMENT
LOWlib/faker/internet.rb381 # Returns Ipv4 address with CIDR, range from 1 to 31COMMENT
LOWlib/faker/internet.rb401 endCOMMENT
LOWlib/faker/internet.rb421 # @param scheme [String]COMMENT
LOWlib/faker/internet.rb441 # Faker::Internet.slug #=> "repudiandae-sed"COMMENT
LOWlib/faker/internet.rb461 endCOMMENT
LOWlib/faker/internet.rb481 ##COMMENT
LOWlib/faker/internet.rb501 # @return [String]COMMENT
LOWlib/faker/internet.rb541COMMENT
LOWlib/faker/music/rush.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/pearl_jam.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/pearl_jam.rb21 # Produces the name of an album by Pearl Jam.COMMENT
LOWlib/faker/music/hiphop.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/hiphop.rb21 # Produces the name of a Hip Hop GroupCOMMENT
LOWlib/faker/music/smashing_pumpkins.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/smashing_pumpkins.rb21 # Produces the name of an album by the Smashing Pumpkins.COMMENT
LOWlib/faker/music/smashing_pumpkins.rb41 #COMMENT
LOWlib/faker/music/prince.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/prince.rb21 ##COMMENT
LOWlib/faker/music/prince.rb41 # Faker::Music::Prince.album #=> "The Gold Experience"COMMENT
LOWlib/faker/music/grateful_dead.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/rock_band.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/phish.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/phish.rb21 # Produces the name of a musician in Phish.COMMENT
LOWlib/faker/music/opera.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/music/opera.rb21 ##COMMENT
LOWlib/faker/music/opera.rb41 #COMMENT
LOWlib/faker/music/opera.rb61 # Produces the title of an opera by Wolfgang Amadeus Mozart.COMMENT
LOWlib/faker/music/opera.rb81 #COMMENT
LOWlib/faker/music/opera.rb101 # Produces the title of an opera by Christoph Willibald Gluck.COMMENT
LOWlib/faker/music/opera.rb121 #COMMENT
LOWlib/faker/music/opera.rb141 # Produces the title of an opera by Ludwig van Beethoven.COMMENT
LOWlib/faker/music/opera.rb161 # @faker.version nextCOMMENT
LOWlib/faker/music/opera.rb181 #COMMENT
LOWlib/faker/music/opera.rb201 def schumannCOMMENT
LOWlib/faker/music/opera.rb221 # @return [String]COMMENT
LOWlib/faker/music/opera.rb241 fetch('opera.french.by_maurice_ravel')COMMENT
LOWlib/faker/music/opera.rb261 #COMMENT
LOWlib/faker/music/bossa_nova.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/quotes/chiquito.rb1# frozen_string_literal: trueCOMMENT
LOWlib/faker/quotes/chiquito.rb21 # Produces a concept from ChiquitoCOMMENT
LOWlib/faker/quotes/chiquito.rb41 #COMMENT
LOWlib/faker/quotes/shakespeare.rb1# frozen_string_literal: trueCOMMENT
676 more matches not shown…
Hyper-Verbose Identifiers16 hits · 18 pts
SeverityFileLineSnippetContext
LOWtest/faker/default/test_faker_id_number.rb279 def assert_valid_south_african_id_number(sample)CODE
LOWlib/faker/internet.rb564 def sanitize_email_local_part(local_part)CODE
LOWlib/faker/default/id_number.rb296 def croatian_id_checksum_digit(digits)CODE
LOWlib/faker/default/id_number.rb311 def chilean_verification_code(digits)CODE
LOWlib/faker/default/id_number.rb331 def south_african_id_checksum_digit(id_number)CODE
LOWlib/faker/default/id_number.rb349 def brazilian_citizen_number_checksum_digit(digits)CODE
LOWlib/faker/default/id_number.rb354 def brazilian_id_checksum_digit(digits)CODE
LOWlib/faker/default/id_number.rb359 def brazilian_document_checksum(digits)CODE
LOWlib/faker/default/id_number.rb370 def brazilian_citizen_number_digit(remainder)CODE
LOWlib/faker/default/barcode.rb30 def ean_with_composite_symbology(length = 8)CODE
LOWlib/faker/default/measurement.rb141 def define_measurement_locale(amount, locale)CODE
LOWlib/faker/default/code.rb283 def generate_nric_check_alphabet(values, prefix)CODE
LOWlib/faker/default/company.rb178 def spanish_organisation_number(organization_type: nil)CODE
LOWlib/faker/default/company.rb325 def polish_register_of_national_economy(length: 9)CODE
LOWlib/faker/default/company.rb639 def spanish_cif_control_digit(organization_type, code)CODE
LOWlib/faker/travel/train_station.rb29 def fill_missing_inputs_with_samples(region, type)CODE
Fake / Example Data6 hits · 6 pts
SeverityFileLineSnippetContext
LOWCHANGELOG.md699* Add exclude_words keyword to Lorem Ipsum to prevent words from being produced by @philipfong in #2665COMMENT
LOWdoc/default/markdown.md5Generates markdown formatting with Lorem Ipsum textCODE
LOWdoc/default/omniauth.md13 :name => "John Doe",CODE
LOWdoc/default/omniauth.md30 :name => "John Doe",CODE
LOWdoc/default/omniauth.md164 "name"=>"John Doe",CODE
LOWdoc/default/omniauth.md166 "nickname"=>"John Doe",CODE
AI Slop Vocabulary2 hits · 4 pts
SeverityFileLineSnippetContext
LOWtest/faker/default/test_array_sample_method_compat.rb8# Under Ruby 1.9, they simply use the built-in Array#sample methodCOMMENT
MEDIUMlib/faker/default/company.rb79 # Faker::Company.bs #=> "empower customized functionalities"COMMENT
Redundant / Tautological Comments1 hit · 2 pts
SeverityFileLineSnippetContext
LOWlib/faker/default/company.rb480 # Check if state code is validCOMMENT
Slop Phrases1 hit · 1 pts
SeverityFileLineSnippetContext
LOWlib/locales/en/heroes_of_the_storm.yml116 - Don't forget to check the pocket!CODE