PropWise
An AST-based analyzer for identifying property-based testing candidates in Elixir codebases.
Overview
PropWise analyzes your Elixir code to find functions that would benefit from property-based testing. It examines the Abstract Syntax Tree (AST) of your code to:
- Detect pure functions (functions without side effects)
- Identify common patterns suitable for property testing
- Find inverse function pairs (encode/decode, serialize/deserialize, etc.)
- Score and rank candidates by testability
- Provide specific testing suggestions for each candidate
Features
Purity Analysis
Detects side effects by analyzing function calls:
- I/O operations (File, IO)
- Process operations (GenServer, Agent, Task)
- Database operations (Ecto)
- HTTP requests
- System calls
- Message passing
Pattern Detection
Identifies functions with characteristics ideal for property testing:
- Collection Operations: Functions using Enum, Stream, or list comprehensions
- Data Transformations: Struct update and map write operations
- Validation Functions: Functions following naming conventions (
?suffix,valid/check/is_prefix) - Algebraic Structures: Merge, concat, union, compose, and other potentially algebraic operations
- Encoders/Decoders: Serialization and encoding/decoding functions
- Numeric Algorithms:
:mathmodule calls, kernel numeric functions, and significant arithmetic (2+ operations)
Inverse Pair Detection
Finds function pairs that are inverses of each other:
- encode/decode
- serialize/deserialize
- parse/format or parse/generate
- compress/decompress
- encrypt/decrypt
- to*/from*
- pack/unpack
- marshal/unmarshal
Concrete Test Generation
Generates ready-to-use property-based test code:
-
Supports multiple libraries:
stream_data(default) andPropEr - Specific test properties tailored to detected patterns
- Complete test blocks with appropriate generators
- Assertions matching the function's expected behavior
- Copy-paste ready test code to get started quickly
Installation
As a Library
Add propwise to your list of dependencies in mix.exs:
def deps do
[
{:propwise, "~> 0.2"}
]
endAs a Command-Line Tool
Option 1: escript (Recommended for standalone use)
Build and install the standalone executable:
cd propwise
mix deps.get
mix escript.build
# Copy to a directory in your PATH
sudo cp propwise /usr/local/bin/
# Or just use it directly
./propwiseThe escript bundles all dependencies and works without Mix or any additional setup.
Option 2: Mix archive
Install globally from Hex as a Mix archive:
mix archive.install hex propwise
This makes the mix propwise task available in any project. Note: This requires jason to be available in your Mix environment.
To uninstall:
mix archive.uninstall propwiseOption 3: As a dependency
When added as a project dependency, PropWise provides a Mix task:
mix propwiseUsage
Command Line
Using escript
# Analyze current project
./propwise .
# Analyze with custom minimum score
./propwise --min-score 5 ./my_project
# Output as JSON
./propwise --format json ./my_project
# Use PropEr instead of stream_data
./propwise --library proper ./my_project
# Show help
./propwise --helpUsing Mix task
# Analyze current project
mix propwise
# Analyze with custom minimum score
mix propwise --min-score 5
# Output as JSON
mix propwise --format json
# Use PropEr instead of stream_data
mix propwise --library proper
# Analyze another project
mix propwise ../other_project
# Show help
mix propwise --helpAs a Library
# Analyze a project
result = PropWise.analyze("./my_project")
# Analyze with custom options
result = PropWise.analyze("./my_project", min_score: 5, library: :proper)
# Print the report
PropWise.print_report(result)
# Print as JSON
PropWise.print_report(result, format: :json)Example Output
================================================================================
PropWise Analysis Report
================================================================================
Summary:
Total functions analyzed: 143
Property test candidates: 24
Candidates dropped (below threshold): 12
Coverage: 16.8%
--------------------------------------------------------------------------------
Inverse Function Pairs Detected:
--------------------------------------------------------------------------------
MyApp.Encoder.encode/1 <-> decode/1
Suggestion: Test round-trip property: decode(encode(x)) == x
--------------------------------------------------------------------------------
Top Candidates (sorted by score):
--------------------------------------------------------------------------------
MyApp.Parser.parse_json/1
Score: 6
Location: lib/my_app/parser.ex:42
Type: public
Patterns:
- Parser: Parser function
Testing suggestions:
- property "parse returns expected structure" do
check all input <- string(:alphanumeric) do
case Parser.parse_json(input) do
{:ok, result} ->
# TODO: Add structural assertions for parsed output.
assert result != nil
{:error, _} -> true
end
end
end
MyApp.List.merge_sorted/2
Score: 8
Location: lib/my_app/list.ex:15
Type: public
Patterns:
- Collection Operation: Uses Enum collection operations
- Algebraic Structure: Potentially algebraic operation
Testing suggestions:
- property "associativity" do
check all a <- term(), b <- term(), c <- term() do
assert List.merge_sorted(List.merge_sorted(a, b), c) ==
List.merge_sorted(a, List.merge_sorted(b, c))
end
endScoring System
Functions are scored based on multiple factors:
- Base score: 1 point for pure functions
- Pattern detection: 2 points per detected pattern
- Multiple patterns: 2 bonus points for functions with 2+ patterns
- Complexity: 1 bonus point for non-trivial functions
- Visibility: 1 bonus point for public functions
Default minimum score is 4, but this can be adjusted based on your needs.
For detailed information about all detection criteria and scoring rules, see Scoring.
Configuration
You can customize PropWise's behavior by creating a .propwise.exs file in your project root.
Example Configuration
# .propwise.exs
%{
# Directories to analyze (relative to project root)
# Default: ["lib"]
analyze_paths: ["lib"],
# Property-based testing library to use for suggestions
# Options: :stream_data (default) or :proper
library: :stream_data
# You can analyze multiple directories:
# analyze_paths: ["lib", "src", "apps/my_app/lib"]
}Configuration Options
analyze_paths- List of directories to analyze relative to project root (default:["lib"])library- Property testing library for code generation::stream_dataor:proper(default::stream_data)
If no .propwise.exs file is present, PropWise will use the defaults.
Options
CLI Options
-m, --min-score NUM: Minimum score for candidates (default: 4)-f, --format FORMAT: Output format: text or json (default: text)-o, --output FILE: Write output to file instead of stdout-l, --library LIB: Property testing library: stream_data or proper (default: stream_data)--no-fail: Exit with code 0 even when suggestions are found-h, --help: Show help message
Note: CLI options override configuration file settings.
Library Options
:min_score- Minimum score threshold (integer, default: 4):format- Output format (:textor:json, default::text):library- Property testing library (:stream_dataor:proper, default::stream_data)
How It Works
- Parse: Recursively finds all
.exfiles in configured directories (default:lib) - Extract: Parses each file's AST and extracts function definitions
- Analyze Purity: Walks the AST to detect side effects
- Detect Patterns: Looks for common patterns in function structure and naming
- Score: Calculates a testability score for each function
- Find Pairs: Identifies inverse function pairs across the codebase
- Generate Suggestions: Creates concrete property-based test examples using your chosen library
- Report: Presents findings with ready-to-use test code
Limitations
- Static analysis only - doesn't execute code
- May produce false positives for functions that call other module functions (can't determine if those are pure)
- Pattern detection is heuristic-based
- Doesn't analyze macros or dynamically generated code in depth
Security Note
PropWise loads configuration from .propwise.exs files using Code.eval_file/1,
which executes arbitrary Elixir code. Only analyze projects you trust.
Contributing
Contributions are welcome! Areas for improvement:
- Additional pattern detectors
- Smarter purity analysis (tracking function calls across modules)
- Integration with existing property testing libraries
- IDE integration
License
MIT