Finding the Right Way to Rome: Effect-Oriented Graph Transformation
Paper i proceeding, 2023

Many applications of graph transformation require rules that change a graph without introducing new consistency violations. When designing such rules, it is natural to think about the desired outcome state, i.e., the desired effect, rather than the specific steps required to achieve it; these steps may vary depending on the specific rule-application context. Existing graph-transformation approaches either require a separate rule to be written for every possible application context or lack the ability to constrain the maximal change that a rule will create. We introduce effect-oriented graph transformation, shifting the semantics of a rule from specifying actions to representing the desired effect. A single effect-oriented rule can encode a large number of induced classic rules. Which of the potential actions is executed depends on the application context; ultimately, all ways lead to Rome. If a graph element to be deleted (created) by a potential action is already absent (present), this action need not be performed because the desired outcome is already present. We formally define effect-oriented graph transformation, show how matches can be computed without explicitly enumerating all induced classic rules, and report on a prototypical implementation of effect-oriented graph transformation in Henshin.

Double-pushout approach

Graph transformation

Consistency-preserving transformations

Författare

Jens Kosiol

Philipps-Universität Marburg

Daniel Strüber

Radboud Universiteit

Göteborgs universitet

Gabriele Taentzer

Philipps-Universität Marburg

Steffen Zschaler

King's College London

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 13961 LNCS 43-63
9783031367083 (ISBN)

16th International Conference on Graph Transformation, ICGT 2023
Leicester, United Kingdom,

Ämneskategorier

Datavetenskap (datalogi)

DOI

10.1007/978-3-031-36709-0_3

Mer information

Senast uppdaterat

2023-10-26