Advanced Model Consistency Restoration with Higher-Order Short-Cut Rules
Sequential model synchronisation is the task of propagating changes from one model to another correlated one to restore consistency. It is challenging to perform this propagation in a least-changing way that avoids unnecessary deletions (which might cause information loss). From a theoretical point...
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| Vydané v: | Logical methods in computer science Ročník 20, Issue 3 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Logical Methods in Computer Science e.V
18.09.2024
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| Predmet: | |
| ISSN: | 1860-5974, 1860-5974 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Sequential model synchronisation is the task of propagating changes from one
model to another correlated one to restore consistency. It is challenging to
perform this propagation in a least-changing way that avoids unnecessary
deletions (which might cause information loss). From a theoretical point of
view, so-called short-cut (SC) rules have been developed that enable provably
correct propagation of changes while avoiding information loss. However, to be
able to react to every possible change, an infinite set of such rules might be
necessary. Practically, only small sets of pre-computed basic SC rules have
been used, severely restricting the kind of changes that can be propagated
without loss of information. In this work, we close that gap by developing an
approach to compute more complex required SC rules on-the-fly during
synchronisation. These higher-order SC rules allow us to cope with more complex
scenarios when multiple changes must be handled in one step. We implemented our
approach in the model transformation tool eMoflon. An evaluation shows that the
overhead of computing higher-order SC rules on-the-fly is tolerable and at
times even improves the overall performance. Above that, completely new
scenarios can be dealt with without the loss of information. |
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| ISSN: | 1860-5974 1860-5974 |
| DOI: | 10.46298/lmcs-20(3:25)2024 |