Declarative model transformation execution planning

Research output: Contribution to journalConference articlepeer-review


Declarative model transformation languages require that the underlying reasoning engine synthesises an execution plan that guarantees correctness while also providing reasonable performance. Optimization of these execution plans is a hard problem and for languages such as QVT Core, finding an optimal solution is still unsolved. By understanding how a brute force execution plan guarantees correctness, we can find an algorithm to construct the complete solution space of correct execution plans and from it find an optimal solution. In this paper we explore how the complete solution space of execution plans can be constructed, how data dependency analysis can be used to evaluate these plans for correctness and how their performance can be estimated. The results show that our performance estimates are correlated to the observed performance.

Original languageEnglish
Pages (from-to)105-120
Number of pages16
JournalCEUR Workshop Proceedings
Publication statusPublished - 2016
Event16th International Workshop on OCL and Textual Modelling, OCL 2016 - Saint-Malo, France
Duration: 2 Oct 2016 → …

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