Related papers: Saying Hello World with GROOVE - A Solution to the…

This paper discusses the GReTL solution of the TTC 2011 Hello World case. The submitted solution covers all tasks including the optional ones.

This report presents a partial solution to the Compiler Optimization case study using GROOVE. We explain how the input graphs provided with the case study were adapted into a GROOVE representation and we describe an initial solution for…

This paper gives an overview of the Henshin solution to the Hello World case study of the Transformation Tool Contest 2011, intended to show basic language concepts and constructs.

The paper presents a solution of the Hello World! An Instructive Case for the Transformation Tool Contest using the VIATRA2 model transformation tool.

This paper describes the solution of Hello World transformations in MOLA transformation language. Transformations implementing the task are relatively straightforward and easily inferable from the task specification. The required additional…

This paper gives an overview of the Edapt solution to the hello world case of the Transformation Tool Contest 2011.

We introduce the graph transformation tool GrGen.NET (www.grgen.net) by solving the Hello World Case of the Transformation Tool Contest 2011 which consists of a collection of small transformation tasks; for each task a section is given…

In this short paper we present our solution for the Hello World case study of the Transformation Tool Contest (TTC) 2011 using the QVTR-XSLT tool. The tool supports editing and execution of the graphical notation of QVT Relations language.…

This paper describes the GROOVE solution to the "Class Diagram Restructuring" case study of the Tool Transformation Contest 2013. We show that the visual rule formalism enables the required restructuring to be formulated in a very concise…

Epsilon is an extensible platform of integrated and task-specific languages for model management. With solutions to the 2011 TTC Hello World case, this paper demonstrates some of the key features of the Epsilon Object Language (an extension…

This paper discusses the GReTL solution of the TTC 2011 Compiler Optimization case. The submitted solution covers both the constant folding task and the instruction selection task. The verifier for checking the validity of the graph is also…

This paper discusses the GReTL reference solution of the TTC 2011 Reengineering case. Given a Java syntax graph, a simple state machine model has to be extracted. The submitted solution covers both the core task and the two extension tasks.

The aim of the Transformation Tool Contest (TTC) series is to compare the expressiveness, the usability and the performance of graph and model transformation tools along a number of selected case studies. Participants want to learn about…

This case comprises several primitive tasks that can be solved straight away with most transformation tools. The aim is to cover the most important kinds of primitive operations on models, i.e. create, read, update and delete (CRUD). To…

This paper presents the Henshin solution to the Model Transformations for Program Understanding case study as part of the Transformation Tool Contest 2011.

FunnyQT is a model querying and model transformation library for the functional Lisp-dialect Clojure providing a rich and efficient querying and transformation API. This paper describes the FunnyQT solution to the TTC 2013 Class Diagram…

Counterfactual explanations have been widely studied in explainability, with a range of application dependent methods prominent in fairness, recourse and model understanding. The major shortcoming associated with these methods, however, is…

After 20 years of Triple Graph Grammars (TGGs) and numerous actively maintained implementations, there is now a need for challenging examples and success stories to show that TGGs can be used for real-world bidirectional model…

Users typically interact with and evaluate language models via single outputs, but each output is just one sample from a broad distribution of possible completions. This interaction hides distributional structure such as modes, uncommon…

Word vector representations open up new opportunities to extract useful information from unstructured text. Defining a word as a vector made it easy for the machine learning algorithms to understand a text and extract information from. Word…