Abstract. Since the systematic evolution of graph-like program models has become important in software engineering, graph transformation has gained much attention in this area. For specifying model evolution concisely, graph transformation rules should be as expressive as possible. The generic rules proposed in this paper may contain placeholders for graphs of varying number and shape. Expansion of these placeholders by graphs yields the actual transformation rules to be applied. Even rather complex transformations occurring in real-life applications, such as the Pull-Up-Method refactoring operation, can be specified by a single generic rule. 1

Abstract. The notion of path is classical in graph theory but not directly used in the term rewriting community. The main idea of this work is to raise the notion of path to the level of first-order terms, i.e. paths become part of the terms and not just meta-information about them. These paths are represented by words of integers (positive or negative) and are interpreted as relative addresses in terms. In this way, paths can also be seen as a generalization of the classical notion of position for the first-order terms and are inspired by de Bruijn indexes. In this paper, we define an original framework called Referenced Term Rewriting where paths are used to represent pointers between subterms. Using this approach, any term-graph rewriting systems can be simulated using a term rewrite-based environment. 1

Abstract. Hans-Jörg Kreowski was among the first researchers to point out that P/T Petri nets can be interpreted as instances of Graph Transformation Systems, a fact now considered folklore. We elaborate on this observation, discussing how several different models of Petri nets can be encoded faithfully into Graph Transformation Systems. The key idea we pursue is that the net encoding is uniquely determined, and distinct net models are mapped to alternative approaches to graph transformation. 1

Abstract. E-government services usually process large amounts of confidential data. Therefore, security requirements for the communication between components have to be adhered in a strict way. Hence, it is of main interest that developers can analyze their modularized models of actual systems and that they can detect critical patterns. For this purpose, we present a general and formal framework for critical pattern detection and user-driven correction as well as possibilities for automatic analysis and verification at meta-model level. The technique is based on the formal theory of graph transformation, which we extend to transformations of type graphs with inheritance within a type graph hierarchy. We apply the framework to specify relevant security requirements. The extended theory is shown to fulfil the conditions of a weak adhesive HLR category allowing us to transfer analysis techniques and results shown for this abstract framework of graph transformation. In particular, we discuss how confluence analysis and parallelization can be used to enable parallel critical pattern detection and elimination. 1

Îlots formels et certification du filtrage 31 Gestion mémoire et structures de données 61 Applications 121 Extensions aux anti-patterns et aux graphes 155Présentations de Tom

In this paper, we introduce a novel way of constructing concise causal histories (pathways) to represent how specified structures are formed during simulation of systems represented by rulebased models. This is founded on a new, clean, graph-based semantics introduced in the first part of this paper for Kappa, a rule-based modelling language that has emerged as a natural description of protein-protein interactions in molecular biology [1]. The semantics is capable of capturing the whole of Kappa, including subtle side-effects on deletion of structure, and its structured presentation provides the basis for the translation of techniques to other models. In particular, we give a notion of trajectory compression, which restricts a trace culminating in the production of a given structure to the actions necessary for the structure to occur. This is central to the reconstruction of biochemical pathways due to the failure of traditional techniques to provide adequately concise causal histories, and we expect it to be applicable in a range of other modelling situations.