uvlparser 2.0.1

This module provides a get_tree function to obtain an ANTLR parse-tree from a UVL-defined feature model

UVL - Universal Variability Language

This is a small default library used to parse and print the Universal Variability Language (UVL).

Under the hood it uses ANTLR4 as the parsing library. The grammar in EBNF form is located in uvl/UVL.g4 and the modifications for Java and Python

The Language

On a high level, each feature model in UVL consists of five optional separated elements:

1. A list of used language levels The model can use different concepts which are part of language levels. These levels can either be enumerated with the include keyword or be implicit.
2. A namespace which can be used for references in other models
3. A list of imports that can be used to reference external feature models The models are referenced by their file name and can be given an alias using a Java import like syntax. External models in subdirectories can be referenced like this: subdir.filename as fn
4. The tree hierarchy consisting of: features, group types, and attributes whose relations are specified using nesting (indentation) Groups may have an arbitrary number of features as child nodes. A feature can also have a feature cardinality. Attributes consist of a key-value pair whose key is always a string and its value may be a boolean, number, string, a list attributes, a vector, or a constraint. If the value is a constraint the key must be constraint. If the value is a list of constraints the key must be constraints
5. Cross-tree constraints Cross-tree constraints may be arbitrary propositional formulas with the following symbols: => (implies), <=> (iff), & (and), | (or), ! (not), or brackets. Through the usage of language levels cross-tree constraints can also contain equations (<,>,==) which consist of expressions (+,-,*,/) with numbers or numerical feature attributes as literals and aggregate functions (avg, sum).

The following snippet shows a simplified server architecture in UVL. We provide more examples (e.g., to show the composition mechanism) in https://github.com/Universal-Variability-Language/uvl-models/tree/main/Feature_Models.

namespace Server

features
  Server {abstract}
    mandatory
      FileSystem
        or // with cardinality: [1..*]
          NTFS
          APFS
          EXT4
      OperatingSystem {abstract}
        alternative
          Windows
          macOS
          Debian
    optional
      Logging	{
      default,
      log_level "warn" // Feature Attribute
    }

constraints
  Windows => NTFS
  macOS => APFS

In this snippet, we can recognize the following elements:

• The feature Server is abstract (i.e., corresponds to no implementation artifact.
• Each Server requires a FileSystemand an OperatingSystem denoted by the mandatory group
• The Server may have Logging denoted by the optional group
• A FileSystem requires at least one type of NTFS, APFS, and Ext4 denoted by the or group
• An OperatingSystem has exactly one type of Windows, macOS, and Debiandenoted by the alternative group
• Logging has the feature attribute log_level attached which is set to "warn"
• Windows requires NTFS denoted by the first cross-tree constraint
• macOSrequires APFS

Building a jar

The library is a maven project and can therefore be build with maven. To update the generated parser classes and create a jar with all necessary dependencies, use:

mvn clean compile assembly:single

The target/uvl-parser-1.0-SNAPSHOT-jar-with-dependencies.jar includes all dependencies.

Usage from Java

The class de.vill.main.UVLModelFactory exposes the static method parse(String) which will return an instance of a de.vill.model.FeatureModel class. If there is something wrong, a de.vill.exception.ParseError is thrown. The parser tries to parse the whole model, even if there are errors. If there are multiple errors, a de.vill.exception.ParseErrorList is returned which contains all errors that occurred. A model can be printed with the toString() method of the de.vill.model.FeatureModel object. The following snippet shows a minimal example to read and write UVL models using the jar. More usage examples that also show how to use the acquired UVLModel object can be found in src/main/java/de/vill/main/Example.java

// Read
Path filePath = Paths.get(pathAsString);
String content = new String(Files.readAllBytes(filePath));
UVLModelFactory uvlModelFactory = new UVLModelFactory();
FeatureModel featureModel = uvlModelFactory.parse(content);


// Write
String uvlModel = featureModel.toString();
Path filePath = Paths.get(featureModel.getNamespace() + ".uvl");
Files.write(filePath, uvlModel.getBytes());

Links

UVL models:

• https://github.com/Universal-Variability-Language/uvl-models

Other parsers:

• https://github.com/Universal-Variability-Language/uvl-parser deprecated, Initial UVL Parser, based on Clojure and instaparse UVL-Parser
• https://github.com/diverso-lab/uvl-diverso/ Under development, Antlr4 Parser Diverso Lab

Usage of UVL:

• https://github.com/FeatureIDE/FeatureIDE Feature modelling tool