The TTC 2013 Flowgraphs Case

This case for the Transformation Tool Contest 2013 is about evaluating the scope and usability of transformation languages and tools for a set of four tasks requiring very different capabilities. One task deals with typical model-to-model transformation problem, there's a model-to-text problem, there are two in-place transformation problems, and finally there's a task dealing with validation of models resulting from the transformations. The tasks build upon each other, but the transformation case project also provides all intermediate models, thus making it possible to skip tasks that are not suited for a particular tool, or for parallelizing the work among members of participating teams.Comment: In Proceedings TTC 2013, arXiv:1311.753

Solving the TTC 2011 Reengineering Case with GReTL

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.Comment: In Proceedings TTC 2011, arXiv:1111.440

Saying Hello World with GReTL - A Solution to the TTC 2011 Instructive Case

This paper discusses the GReTL solution of the TTC 2011 Hello World case. The submitted solution covers all tasks including the optional ones.Comment: In Proceedings TTC 2011, arXiv:1111.440

A Functional, Comprehensive and Extensible Multi-Platform Querying and Transformation Approach

This thesis is about a new model querying and transformation approach called FunnyQT which is realized as a set of APIs and embedded domain-specific languages (DSLs) in the JVM-based functional Lisp-dialect Clojure. Founded on a powerful model management API, FunnyQT provides querying services such as comprehensions, quantified expressions, regular path expressions, logic-based, relational model querying, and pattern matching. On the transformation side, it supports the definition of unidirectional model-to-model transformations, of in-place transformations, it supports defining bidirectional transformations, and it supports a new kind of co-evolution transformations that allow for evolving a model together with its metamodel simultaneously. Several properties make FunnyQT unique. Foremost, it is just a Clojure library, thus, FunnyQT queries and transformations are Clojure programs. However, most higher-level services are provided as task-oriented embedded DSLs which use Clojure's powerful macro-system to support the user with tailor-made language constructs important for the task at hand. Since queries and transformations are just Clojure programs, they may use any Clojure or Java library for their own purpose, e.g., they may use some templating library for defining model-to-text transformations. Conversely, like every Clojure program, FunnyQT queries and transformations compile to normal JVM byte-code and can easily be called from other JVM languages. Furthermore, FunnyQT is platform-independent and designed with extensibility in mind. By default, it supports the Eclipse Modeling Framework and JGraLab, and support for other modeling frameworks can be added with minimal effort and without having to modify the respective framework's classes or FunnyQT itself. Lastly, because FunnyQT is embedded in a functional language, it has a functional emphasis itself. Every query and every transformation compiles to a function which can be passed around, given to higher-order functions, or be parametrized with other functions

Program Understanding: A Reengineering Case for the Transformation Tool Contest

In Software Reengineering, one of the central artifacts is the source code of the legacy system in question. In fact, in most cases it is the only definitive artifact, because over the time the code has diverged from the original architecture and design documents. The first task of any reengineering project is to gather an understanding of the system's architecture. Therefore, a common approach is to use parsers to translate the source code into a model conforming to the abstract syntax of the programming language the system is implemented in which can then be subject to querying. Despite querying, transformations can be used to generate more abstract views on the system's architecture. This transformation case deals with the creation of a state machine model out of a Java syntax graph. It is derived from a task that originates from a real reengineering project.Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Compiler Optimization Case with GReTL

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 implemented, and some additional test graphs are provided as requested by the extension.Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with GrGen.NET

The challenge of the Reengineering Case is to extract a state machine model out of the abstract syntax graph of a Java program. The extracted state machine offers a reduced view on the full program graph and thus helps to understand the program regarding the question of interest. We tackle this task employing the general purpose graph rewrite system GrGen.NET (www.grgen.net).Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with VIATRA2

The current paper presents a solution of the Program Understanding: A Reengineering Case for the Transformation Tool Contest using the VIATRA2 model transformation tool.Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with Henshin

This paper presents the Henshin solution to the Model Transformations for Program Understanding case study as part of the Transformation Tool Contest 2011.Comment: In Proceedings TTC 2011, arXiv:1111.440

Solving the TTC 2011 Reengineering Case with MOLA and Higher-Order Transformations

The Reengineering Case of the Transformation Tool Contest 2011 deals with automatic extraction of state machine from Java source code. The transformation task involves complex, non-local matching of model elements. This paper contains the solution of the task using model transformation language MOLA. The MOLA solution uses higher-order transformations (HOT-s) to generate a part of the required MOLA program. The described HOT approach allows creating reusable, complex model transformation libraries for generic tasks without modifying an implementation of a model transformation language. Thus model transformation users who are not the developers of the language can achieve the desired functionality more easily.Comment: In Proceedings TTC 2011, arXiv:1111.440