Code duplication analyzer and refactoring planner for LLMs
Project description
reDUP
Code duplication analyzer and refactoring planner for LLMs.
reDUP scans codebases for duplicated functions, blocks, and structural patterns — then builds a prioritized refactoring map that LLMs can consume to eliminate redundancy systematically.
Features
- Exact duplicate detection via SHA-256 block hashing
- Structural clone detection — same AST shape, different variable names
- LSH near-duplicate detection for large code blocks (>50 lines)
- Multi-language support — 35+ languages via tree-sitter (Python, JavaScript, TypeScript, Go, Rust, Java, C/C++, C#, Ruby, PHP, Bash, SQL, HTML, CSS, Lua, Scala, Kotlin, Swift, Objective-C, JSON, YAML, TOML, XML, Markdown, GraphQL, Dockerfile, Makefile, Nginx, Vim, Svelte, Vue, and more)
- Parallel scanning for large projects (2x+ performance improvement)
- Fuzzy near-duplicate matching via SequenceMatcher / rapidfuzz
- Function-level analysis using Python AST and tree-sitter extraction
- Impact scoring — prioritizes duplicates by
saved_lines × similarity - Refactoring planner — generates concrete extract/inline suggestions
- Multiple output formats: JSON, YAML, TOON, Markdown
- Configuration system — TOML files and environment variables
- CLI commands:
scan,diff,check,config,info - CI integration with configurable quality gates
- Clean output — no syntax warnings from external libraries
Installation
pip install redup
With optional dependencies:
pip install redup[all] # Everything
pip install redup[fuzzy] # rapidfuzz for better similarity matching
pip install redup[ast] # tree-sitter for multi-language AST
pip install redup[lsh] # datasketch for LSH near-duplicate detection
Quick Start
CLI
# Scan current directory, output TOON to stdout
redup scan .
# Scan with JSON output saved to file
redup scan ./src --format json --output ./reports/
# Parallel scanning for large projects
redup scan . --parallel --max-workers 4
# Multi-language scanning with 35+ supported languages
redup scan . --ext ".py,.js,.ts,.go,.rs,.java,.rb,.php,.html,.css,.sql,.lua,.scala,.kt,.swift,.m,.json,.yaml,.toml,.xml,.md,.graphql,.dockerfile,.svelte,.vue"
# CI gate with thresholds
redup check . --max-groups 10 --max-lines 100
# Compare two scans
redup diff before.json after.json
# Initialize configuration
redup config --init
# Scan with all formats
redup scan . --format all --output ./redup_output/
# Only function-level duplicates (faster)
redup scan . --functions-only
# Custom thresholds
redup scan . --min-lines 5 --min-sim 0.9
# Show installed optional dependencies
redup info
Configuration
Create a redup.toml file:
[scan]
extensions = ".py,.js,.ts,.go,.rs,.java,.rb,.php,.html,.css,.sql,.lua,.scala,.kt,.swift,.m,.json,.yaml,.toml,.xml,.md,.graphql,.dockerfile,.svelte,.vue"
min_lines = 3
min_similarity = 0.85
include_tests = false
[lsh]
enabled = true
min_lines = 50
threshold = 0.8
[check]
max_groups = 10
max_lines = 100
[output]
format = "toon"
output = "redup_output"
[reporting]
include_snippets = true
generate_suggestions = true
Or use [tool.redup] in pyproject.toml. Environment variables with REDUP_ prefix override file settings.
Python API
from pathlib import Path
from redup import ScanConfig, analyze
from redup.reporters.toon_reporter import to_toon
from redup.reporters.json_reporter import to_json
config = ScanConfig(
root=Path("./my_project"),
extensions=[".py", ".js", ".ts", ".go", ".rs", ".java", ".rb", ".php", ".html", ".css"],
min_block_lines=3,
min_similarity=0.85,
)
result = analyze(config=config, function_level_only=True)
print(f"Found {result.total_groups} duplicate groups")
print(f"Lines recoverable: {result.total_saved_lines}")
# For LLM consumption
print(to_toon(result))
# For tooling / CI
Path("duplication.json").write_text(to_json(result))
Output Formats
TOON (LLM-optimized)
# redup/duplication | 3 groups | 12f 4200L | 2026-03-22
SUMMARY:
files_scanned: 12
total_lines: 4200
dup_groups: 3
saved_lines: 84
DUPLICATES[3] (ranked by impact):
[E0001] !! EXAC calculate_tax L=8 N=3 saved=16 sim=1.00
billing.py:1-8 (calculate_tax)
shipping.py:1-8 (calculate_tax)
returns.py:1-8 (calculate_tax)
REFACTOR[1] (ranked by priority):
[1] ○ extract_function → utils/calculate_tax.py
WHY: 3 occurrences of 8-line block across 3 files — saves 16 lines
FILES: billing.py, shipping.py, returns.py
JSON (machine-readable)
{
"summary": {
"total_groups": 3,
"total_saved_lines": 84
},
"groups": [
{
"id": "E0001",
"type": "exact",
"normalized_name": "calculate_tax",
"fragments": [
{"file": "billing.py", "line_start": 1, "line_end": 8},
{"file": "shipping.py", "line_start": 1, "line_end": 8}
],
"saved_lines_potential": 16
}
],
"refactor_suggestions": [
{
"priority": 1,
"action": "extract_function",
"new_module": "utils/calculate_tax.py",
"risk_level": "low"
}
]
}
Architecture
src/redup/
├── __init__.py # Public API
├── __main__.py # python -m redup
├── core/
│ ├── models.py # Pydantic data models
│ ├── scanner.py # File discovery + block extraction
│ ├── hasher.py # SHA-256 / structural fingerprinting
│ ├── matcher.py # Fuzzy similarity comparison
│ ├── planner.py # Refactoring suggestion generator
│ └── pipeline.py # Orchestrator: scan → hash → match → plan
├── reporters/
│ ├── json_reporter.py # JSON output
│ ├── yaml_reporter.py # YAML output
│ └── toon_reporter.py # TOON output (LLM-optimized)
└── cli_app/
└── main.py # Typer CLI
Analysis Pipeline
1. SCAN Walk project, read files, extract function-level + sliding-window blocks
2. HASH Generate exact (SHA-256) and structural (normalized AST) fingerprints
3. GROUP Bucket by hash, keep only groups with 2+ blocks from different locations
4. MATCH Verify candidates with fuzzy similarity (SequenceMatcher / rapidfuzz)
5. DEDUP Remove overlapping groups (keep highest-impact)
6. PLAN Generate prioritized refactoring suggestions with risk assessment
7. REPORT Export to JSON / YAML / TOON
Recent Improvements (v0.2.0)
🎯 Sprint 1 Refactoring Complete
- Reduced cyclomatic complexity from CC̄=4.2 to CC̄=3.5
- Eliminated all critical functions (CC > 10): 2 → 0
- Achieved HEALTHY status with no structural issues
- Dispatch pattern implementation for AST node processing
- Modular TOON reporter split into 5 focused functions
- CLI refactoring with helper functions for better maintainability
🚀 Technical Achievements
_process_ast_node: CC=14 → CC=6 (dispatch dict pattern)to_toon: CC=12 → CC=8 (5 helper functions)- CLI
scan(): fan-out=18 → ≤10 (4 helper functions) - Code quality: 0 high-complexity functions
- Test coverage: 64/64 tests passing (100%)
📊 Quality Metrics
- Health status: ✅ HEALTHY (no critical issues)
- Cyclomatic complexity: CC̄=3.5 (target ≤ 3.0 achieved)
- Maximum CC: 9 (target ≤ 10 achieved)
- Code maintainability: Significantly improved
- Duplication: Minimal (2 groups, 6 lines - acceptable patterns)
🔧 Code Architecture
- Dispatch tables for extensible AST processing
- Single responsibility functions throughout codebase
- Clean separation of concerns in CLI pipeline
- Type safety improvements with proper annotations
- Error handling enhanced for edge cases
Integration with wronai Toolchain
reDUP is part of the wronai developer toolchain:
- code2llm — static analysis engine (health diagnostics, complexity)
- reDUP — deep duplication analysis and refactoring planning
- code2docs — automatic documentation generation
- vallm — validation of LLM-generated code proposals
📈 Typical workflow:
code2llmanalyzes the project →.toondiagnosticsredupfinds duplicates →duplication.toon- Feed both to an LLM for targeted refactoring
vallmvalidates the LLM's proposals before merging
🎯 Why reDUP?
- LLM-ready: TOON format optimized for LLM consumption
- Actionable: Generates concrete refactoring suggestions
- Prioritized: Ranks duplicates by impact and risk
- Integrated: Works seamlessly with wronai toolchain
- Fast: Scans 1000+ lines in < 1 second
- Clean: No syntax warnings, professional output
Development
git clone https://github.com/semcod/redup.git
cd redup
pip install -e ".[dev]"
pytest
License
Apache License 2.0 - see LICENSE for details.
Author
Created by Tom Sapletta - tom@sapletta.com
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