Well-structured graph transformation systems

König, Barbara; Stückrath, Jan

doi:10.1016/j.ic.2016.03.005

Cited by 5 publications

(20 citation statements)

References 21 publications

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“…A directed, labeled graph consists of a set of nodes and a set of edges where each edge is equipped with a source and a target node and where each node and edge is equipped with a label. Note that this kind of graphs are a special case of the hypergraphs considered in [10].…”

Section: Graph Transformation Systemsmentioning

confidence: 99%

“…We use the single pushout (SPO) approach [6,10] with injective matches for modeling graph transformations. The reason for choosing SPO and not, e.g., the double pushout approach (DPO) [5] is that the dangling condition disturbs the compatibility condition in Def.…”

Section: Fact 1 (Upward and Downward Inheritance) Let G ֒→ H Be A Tot...mentioning

confidence: 99%

“…While several problems are undecidable for transition systems in general due to their infinite state space, many interesting decidability results can be achieved if the system is well-structured [8,1,10].…”

Section: Well-structurednessmentioning

confidence: 99%

“…Usually, the state set (the set of graphs reachable from a start graph) is infinite. To handle infinite state sets, we incorporate the concept of well-structuredness [1,8,10]. A wellstructured transition system (WSTS) is informally a transition system equipped with a well-quasi-order (wqo) satisfying that larger states simulate smaller states.…”

Section: Introductionmentioning

confidence: 99%

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Resilience of Well-structured Graph Transformation Systems

Özkan,

Würdemann

2021

Preprint

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Resilience is a concept of rising interest in computer science and software engineering. For systems in which correctness w.r.t. a safety condition is unachievable, fast recovery is demanded. We investigate resilience problems of graph transformation systems. Our main contribution is the decidability of two resilience problems for well-structured graph transformation systems (with strong compatibility). We prove our results in the abstract framework of well-structured transition systems and apply them to graph transformation systems, incorporating also the concept of adverse conditions. * Supported by the German Research Foundation (DFG) through the Research Training Group (DFG GRK 1765) SCAREWe consider graph constraints [15,9] whose validities are inherited to bigger/smaller graphs.Definition 2 (positive & negative basic graph constraints). The class of positive (basic graph) constraints is defined inductively: (i) ∃G is a positive constraint where G is a graph, (ii) for positive constraints c, c ′ , also c ∨ c ′ , c ∧ c ′ are positive constraints. Analogously, the negative (basic graph) constraints are defined by: (i) ¬∃G is a negative constraint for any graph G, (ii) for negative constraints c, c ′ , also c ∨ c ′ , c ∧ c ′ are negative constraints. A graph G satisfies ∃G ′ if there exists an total injective morphism G ′ ֒→ G. The semantics of the logical operators are as usual. We write G |= c if G satisfies the positive/negative constraint c.

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Section: Graph Transformation Systemsmentioning

confidence: 99%

Section: Fact 1 (Upward and Downward Inheritance) Let G ֒→ H Be A Tot...mentioning

confidence: 99%

Section: Well-structurednessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Resilience of Well-structured Graph Transformation Systems

Özkan,

Würdemann

2021

Preprint

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“…1: construction of the joint system In contrast to other approaches, the constructed joint system is in the same class as the system and the environment, i.e., a graph transformation system. This can be advantageous for transfering well-known concepts for graph transformation systems such as model checking [16] and well-structuredness [17] into this framework.…”

Section: Introductionmentioning

confidence: 99%

Modeling Adverse Conditions in the Framework of Graph Transformation Systems

Özkan

2020

Electron. Proc. Theor. Comput. Sci.

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The concept of adverse conditions addresses systems interacting with an adversary environment and finds use also in the development of new technologies. We present an approach for modeling adverse conditions by graph transformation systems. In contrast to other approaches for graphtransformational interacting systems, the presented main constructs are graph transformation systems. We introduce joint graph transformation systems which involve a system, an interfering environment, and an automaton modeling their interaction. For joint graph transformation systems, we introduce notions of (partial) correctness under adverse conditions, which contain the correctness of the system and a recovery condition. As main result, we show that two instances of correctness, namely k-step correctness (recovery in at most k steps after an environment intervention) and last-minute correctness (recovery until next environment intervention) are expressible in LTL (linear temporal logic), and that a weaker notion of k-step correctness is expressible in CTL (computation tree logic).

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Decidability of Resilience for Well-Structured Graph Transformation Systems

Özkan

2022

Graph Transformation

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Well-structured graph transformation systems

Cited by 5 publications

References 21 publications

Resilience of Well-structured Graph Transformation Systems

Resilience of Well-structured Graph Transformation Systems

Modeling Adverse Conditions in the Framework of Graph Transformation Systems

Decidability of Resilience for Well-Structured Graph Transformation Systems

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