Performance in Model Transformations: Experiments with ATL and QVT

Abstract

Model transformations are increasingly being incorporated in software development processes. However, as systems being developed with transformations grow in size and complexity, the performance of the transformations tends to degrade. In this paper we investigate the factors that have an impact on the execution performance of model transformations. We analyze the performance of three model transformation language engines, namely ATL, QVT Operational Mappings and QVT Relations. We implemented solutions to two transformation problems in these languages and compared the performance of these transformations. We extracted metric values from the transformations to systematically analyze how their characteristics influence transformation execution performance. We also implemented a solution to a transformation problem in ATL in three functionally equivalent ways, but with different language constructs to evaluate the effect of language constructs on transformation performance. The results of this paper enable a transformation designer to estimate beforehand the performance of a transformation, and to choose among implementation alternatives to achieve the best performance. In addition, transformation engine developers may find some of our results useful in order to tune their tools for better performance. This work has been carried out as part of the FALCON project under the responsibility of the Embedded Systems Institute with Vanderlande Industries as the industrial partner. This project is partially supported by the Netherlands Ministry of Economic Affairs under the Embedded Systems Institute (BSIK03021) program.

Towards Model-Based Optimisation: Using Domain Knowledge Explicitly

“…Depending on the size of the models, model transformations can be computationally expensive to execute. There has been recent interest in increasing the efficiency of model transformation execution [26,27]. We need to explore how this could be integrated into model-based optimisation.…”

Model Refinement in the Model Driven Architecture Context

“…ATL is part of the Eclipse Modeling Framework (EMF), a modeling framework for the design of tools based on structured data models (Amstel et al, 2011). In addition, ATL accepts several models as input in the transformation process.…”

“…Execution modes, structure, benefits and technical limitations are thus described. (Amstel et al, 2011).…”

Causal Models for Well-Being

“…In this case, the domain is the manipulation of models represented in a language that adheres to a certain metamodel. We have opted for the use of a domain specific language, choosing the Atlas Transformation Language (ATL) [12,111], as this language has shown to be the fastest performing among current model transformation languages [118]. Additionally, ATL has an active development community of users and is well maintained.…”

“…The ATL editor and transformation engine are provided as an Eclipse plug-ins. ATL outperforms other model transformation engines and has an active community [118]. For the model-to-text transformations, we opted for the use of the Epsilon Generation Language (EGL).…”