Flamapy.js is a JavaScript package designed to bring Flamapy functionalities into a WebAssembly (WASM) environment using Pyodide. It allows developers to work with feature models, variability analysis, and other Flamapy modules directly in JavaScript applications.
- Run Flamapy in a WASM environment without requiring a Python backend.
- Supports multiple Flamapy plugins, such as FlamaPy-SAT, FlamaPy-BDD, and FlamaPy-FM.
- Works seamlessly with Pyodide for efficient execution of Python-based variability models.
Flamapy.js is distributed as an NPM package. You can install it using:
npm install @lbdudc/flamapy.jsimport { Flamapy } from '@lbdudc/flamapy.js';
import { TYPE_SOLVING } from '@lbdudc/flamapy.js/lib/type.js';
// OPTIONAL: Set the options for Flamapy
const options = {
DEBUG: false,
};
const filePath = 'path/to/feature-model.uvl';
// Create a new instance of Flamapy
const flamapy = new Flamapy(filePath, options);
await flamapy.initialize();
try {
// Execute a Flamapy operation
const result = await flamapy.atomicSets();
console.log('Atomic Sets:', result);
} catch (error) {
console.error('Error:', error.message);
}
//For advanced solving types
try {
// Execute a Flamapy operation
const result = await flamapy.coreFeatures(TYPE_SOLVING.PYSAT);
console.log('Core Features:', result);
} catch (error) {
console.error('Error:', error.message);
}Below is a detailed list of supported operations, including their descriptions, inputs, and outputs:
| Method | Description | Inputs | Outputs |
|---|---|---|---|
| Constructor | Creates a new instance of the Flamapy class. |
filepathOrText (string): Path to a feature model file or plain text in UVL format.options (object, optional): Configuration options (e.g., { DEBUG: true }). |
A new Flamapy instance. |
| atomicSets() | Returns the atomic sets of the feature model. | None | Array<Array<string>> – A list of atomic sets. |
| averageBranchingFactor() | Computes the average number of child features per parent feature in the feature model. | None | Number – The average branching factor. |
| commonality(pathToCompare) | Calculates the percentage of features common to both the loaded feature model and another model. | pathToCompare (string): Path to the configuration file or its content. |
Number – The percentage of common features. |
| configurations(typeSolving) | Retrieves a list of all valid configurations in the model. | typeSolving (enum): Type of solving technique (e.g., BASIC, PYSAT, or BDD). |
Array<Object> – A list of valid configurations. |
| configurationsNumber(typeSolving) | Returns the total number of valid configurations. | typeSolving (enum): Type of solving technique (e.g., BASIC, PYSAT, or BDD). |
Number – The total number of configurations. |
| conflictDetection() | Detects conflicts in the feature model. | None | (TODO) |
| coreFeatures(typeSolving) | Returns the list of core features (those present in all configurations). | typeSolving (enum): Type of solving technique (e.g., BASIC or PYSAT). |
Array<string> – A list of core features. |
| countLeafs() | Returns the number of leaf features in the model. | None | Number – The count of leaf features. |
| deadFeatures(typeSolving) | Returns the features that are never selected in any configuration. | typeSolving (enum): Type of solving technique (e.g., BASIC or PYSAT). |
Array<string> – A list of dead features. |
| estimatedNumberOfConfigurations() | Estimates the total number of different configurations that can be produced. | None | Number – The estimated number of configurations. |
| falseOptionalFeatures(typeSolving) | Identifies optional features that behave like mandatory ones in all configurations. | typeSolving (enum): Type of solving technique (e.g., BASIC or PYSAT). |
Array<string> – A list of false optional features. |
| featureAncestors(featureName) | Identifies all ancestor features of a given feature in the feature model. | featureName (string): The name of the feature. |
Array<string> – A list of ancestor features. |
| filterFeatures(path, typeSolving) | Filters and returns a subset of features based on specific criteria. | path (string): Path to the configuration file or its content.typeSolving (enum): Type of solving technique (e.g., BASIC or PYSAT). |
Array<Array<string>> – A filtered list of features. |
| leafFeatures() | Returns all leaf features in the feature model. | None | Array<string> – A list of leaf features. |
| maxDepth() | Computes the maximum depth of the feature tree. | None | Number – The maximum depth. |
| satisfiable(typeSolving) | Checks whether the feature model is valid according to its constraints. | typeSolving (enum): Type of solving technique (e.g., BASIC or PYSAT). |
Boolean – true if the model is satisfiable. |
| satisfiableConfiguration(path, fullConfig, typeSolving) | Checks if there exists at least one valid configuration that satisfies a given set of features. | path (string): Path to the configuration file or its content.fullConfig (boolean): Whether to expect a full configuration or partial.typeSolving (enum): Type of solving technique. |
Boolean – true if a satisfiable configuration exists. |
| uniqueFeatures() | Identifies features that are unique to specific configurations. | None | (TODO) |
If you want to contribute to Flamapy.js, please follow these steps:
- Fork the repository.
- Create a new branch for your feature.
- Submit a pull request with a detailed description of your changes.
A significant part of this project was developed by the Database Laboratory of the University of A Coruña (LBD). You can find more information about their work and other projects at the following links:
- LBD GitHub: https://github.com/lbdudc
- LBD Website: https://lbd.udc.es
-
Victor Lamas
Email: [email protected] -
Maria Isabel Limaylla
Email: [email protected] -
David Organvidez
Email: [email protected]
Flamapy.js is released under the MIT License.
For support or inquiries, open an issue on the GitHub repository or contact the development team.