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Core framework for traceability link recovery between architecture documentation and models while identifying inconsistencies.

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ArDoCo/Core

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ArDoCo Core

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The goal of this project is to connect architecture documentation and models while identifying missing or deviating elements (inconsistencies). An element can be any representable item of the model, like a component or a relation. To do so, we first create trace links and then make use of them and other information to identify inconsistencies.

ArDoCo is actively developed by researchers of the Modelling for Continuous Software Engineering (MCSE) group of KASTEL - Institute of Information Security and Dependability at the KIT.

User Interfaces

To be able to execute the core algorithms from this repository, you can write own user interfaces that (should) use the ArDoCoRunner.

We provide an example Command Line Interface (CLI) at ArDoCo/CLI.

Future user interfaces like a Graphical User Interface (GUI) or a web interface are planned for the future.

Documentation

For more information about the setup or the architecture have a look on the docs. The docs are at some points deprecated, the general overview and setup should still hold. You can find the generated JavaDocs at ArDoCo.github.io/Core-Docs.

Case Studies / Benchmarks

To test the Core, you could use case studies and benchmarks provided in ..

Maven

<dependencies>
	<dependency>
		<groupId>io.github.ardoco.core</groupId>
		<artifactId>pipeline</artifactId> <!-- or any other subproject -->
		<version>0.7.0-SNAPSHOT</version>
	</dependency>
</dependencies>

For snapshot releases, make sure to add the following repository

<repositories>
	<repository>
		<releases>
			<enabled>false</enabled>
		</releases>
		<snapshots>
			<enabled>true</enabled>
		</snapshots>
		<id>mavenSnapshot</id>
		<url>https://s01.oss.sonatype.org/content/repositories/snapshots</url>
	</repository>
</repositories>

Attribution

The initial version of this project is based on the master thesis Linking Software Architecture Documentation and Models.

Acknowledgements

This work was supported by funding from the topic Engineering Secure Systems of the Helmholtz Association (HGF) and by KASTEL Security Research Labs (46.23.01).