Repeated Phrase & Cliché Finder
Repeated Phrase & Cliché Finder: Extracts n-grams (length 2-5) and counts identical contiguous phrase matches.
About this repeated phrase & cliché finder
Extracts n-grams (length 2-5) and counts identical contiguous phrase matches Applies Unicode-compliant text transformations and parsing directly in the browser tab without data leakage.
Text processing & transformation mechanics
Lowercases Unicode letter/number token runs, counts exact contiguous repeated 2–5-token phrases, and returns phrase/count JSON. It does not detect semantic clichés or paraphrases.
Worked text manipulation example
Scenario: Find every repeated contiguous 2–5-token phrase.
Sample input:
Processing: Lowercase token runs and count each n-gram length that can repeat.
Illustrative output:
Character encoding & string length boundaries
This counts exact token sequences, not semantic clichés or paraphrases. Punctuation and CJK segmentation affect phrases.
Text formatting and transformations in Repeated Phrase & Cliché Finder preserve character integrity. Check edge cases such as multi-line inputs and special characters before downstream use.
In-memory text processing boundary
String operations and Unicode manipulations in Repeated Phrase & Cliché Finder execute entirely in local browser memory without transmitting input text.
Unicode Consortium & text formatting standards
Unicode Consortium standard annexes (UAX) and character encoding specifications:
- ECMAScript Unicode letter and number property matching.
- Local exact contiguous 2–5-token n-gram count, further capped at half the input token count; not semantic cliché detection.
Operating System & Terminal CLI Interoperability Protocols
For systems engineers, DevOps practitioners, and backend developers integrating this workflow into automated Continuous Integration (CI/CD) pipelines, crontabs, or shell environments, the client-side algorithms executed by Repeated Phrase & Cliché Finder map directly to native operating-system toolchains:
- Linux & macOS POSIX Terminal Environments: In POSIX environments, execute stream manipulation using GNU/BSD core utilities: `sed -E 's/[[:space:]]+/ /g' input.txt` for whitespace normalization, `tr -d '\r' < dos.txt > unix.txt` for CRLF stripping, and `uconv -x any-nfc input.txt` for Unicode NFC canonical decomposition. For structural text comparison, run `diff -u --color=always file1.txt file2.txt` when you need a conventional unified diff; its output is not claimed to match every browser tool.
- Windows 11 / 10 PowerShell 7+ & Command Environments: In Windows PowerShell, perform multi-line text transformations via `(Get-Content -Raw file.txt) -replace '\r\n', '`n' | Set-Content -NoNewline -Encoding utf8 output.txt`. When matching Unicode category properties, utilize .NET regex classes via `[regex]::Matches($text, '\p{L}+')` to capture alphabetic characters across Latin, Cyrillic, CJK, and Arabic scripts.
- Browser Runtime Sandboxing & Resource Allocation: Text processing algorithms operate over JavaScript UTF-16 strings using standard Unicode Annex #15 normalization and the Intl.Segmenter API for grapheme cluster boundaries. Backtracking regex operations are bounded by execution timeouts to mitigate catastrophic backtracking (ReDoS) vulnerabilities.
Diagnostic Failure Modes & Edge-Case Recovery
When unexpected inputs or boundary conditions occur during data processing, consult this structured diagnostic recovery matrix:
| Fault Condition | Observed Symptom | Engineering Remediation Procedure |
|---|---|---|
| Catastrophic regex backtracking (ReDoS) | Execution timeout warning banner | Refactor nested quantifiers such as (a+)+ into atomic groups or possessive quantifiers (a++) to prevent exponential O(2^n) branch evaluation. |
| Surrogate pair truncation in multi-byte emoji sequences | Replacement character (U+FFFD) or broken grapheme rendering | Iterate across text using Array.from(text) or Intl.Segmenter rather than index-based character slicing to preserve 32-bit astral plane codepoints. |
| Encoding mismatch between UTF-8 and ISO-8859-1 (Latin-1) | Mojibake corruption (e.g., mismatched byte sequences instead of accented glyphs) | Ensure both source file read streams and destination output buffers declare explicit UTF-8 encoding. |
Repeated Phrase & Cliché Finder verification · Audit standards
How to use it
- Paste text.
- Lowercase Unicode letter/number runs, count repeated contiguous phrases of two to five tokens.
- Read phrase/count JSON sorted by length and frequency.
Frequently asked questions
What phrase lengths does Repeated Phrase Finder examine?+
It lowercases Unicode letter-or-number tokens and counts every contiguous phrase from two words through five words, limited further by half of the token count.
What does the example input produce?+
For `one two one two`, the JSON result includes the repeated phrase `one two` with `count: 2`.
How are phrase results ordered?+
It filters to counts above one, then sorts longer phrases first, higher counts next, and finally uses the browser’s `localeCompare` ordering for phrase text.
Does it recognize paraphrases or punctuation differences?+
It ignores punctuation while tokenizing, but compares only exact lowercased token sequences. Synonyms, stemming, language morphology, quotations, and semantic duplication are outside its detection.