Graph rewriting: an algebraic and logic approach
Handbook of theoretical computer science (vol. B)
A framework for the verification of infinite-state graph transformation systems
Information and Computation
ICGT '08 Proceedings of the 4th international conference on Graph Transformations
Towards the Verification of Attributed Graph Transformation Systems
ICGT '08 Proceedings of the 4th international conference on Graph Transformations
Correctness of high-level transformation systems relative to nested conditions†
Mathematical Structures in Computer Science
The Graph Programming Language GP
CAI '09 Proceedings of the 3rd International Conference on Algebraic Informatics
Verification of Sequential and Concurrent Programs
Verification of Sequential and Concurrent Programs
Compositional Verification of Architectural Refactorings
Architecting Dependable Systems VI
Verification of graph transformation systems with context-free specifications
ICGT'10 Proceedings of the 5th international conference on Graph transformations
A hoare calculus for graph programs
ICGT'10 Proceedings of the 5th international conference on Graph transformations
Weakest preconditions for high-level programs
ICGT'06 Proceedings of the Third international conference on Graph Transformations
Hoare-Style Verification of Graph Programs
Fundamenta Informaticae - Recent Developments in the Theory of Graph Transformation, 2010
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GP (for Graph Programs) is an experimental nondeterministic programming language which allows for the manipulation of graphs at a high level of abstraction [11]. The program states of GP are directed labelled graphs. These are manipulated directly via the application of (conditional) rule schemata, which generalise double-pushout rules with expressions over labels and relabelling. In contrast with graph grammars, the application of these rule schemata is directed by a number of simple control constructs including sequential composition, conditionals, and as-long-as-possible iteration. GP shields programmers at all times from low-level implementation issues (e.g. graph representation), and with its nondeterministic semantics, allows one to solve graph-like problems in a declarative and natural way.