Download Applications of Graph Transformations with Industrial by Mario Michele Gala, Elisa Quintarelli, Letizia Tanca PDF

By Mario Michele Gala, Elisa Quintarelli, Letizia Tanca (auth.), John L. Pfaltz, Manfred Nagl, Boris Böhlen (eds.)

This booklet constitutes the completely refereed post-proceedings of the second one foreign Workshop on functions of Graph alterations with commercial Relevance, AGTIVE 2003, held in Charlotesville, Virginia, united states in September/October 2003.

The 27 revised complete papers and eleven revised demo papers offered including 2 invited papers and five workshop experiences have been rigorously chosen in the course of iterated rounds of reviewing and revision. The papers are prepared in topical sections on net purposes; facts constructions and information bases; engineering purposes; agent-oriented and sensible courses and distribution; item- and aspect-oriented platforms; common languages: processing and structuring; reengineering; reuse and integration; modeling languages; bioinformatics; and multimedia, photo, and visible languages.

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Additional info for Applications of Graph Transformations with Industrial Relevance: Second International Workshop, AGTIVE 2003, Charlottesville, VA, USA, September 27 - October 1, 2003, Revised Selected and Invited Papers

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Definitions 2, 3 and 4 below are consistent with the double-pushout approach to defining labelled graphs, morphisms, rules and derivations (see [10]; [11] considers graph relabelling). Fig. 3 shows two example graphs over Definition 2 (Graph) A graph over consists of: a finite set of vertices a finite set of edges total functions assigning a source and target vertex to each edge; a partial node labelling function (a partial function maps domf, a subset of A, to B. We write when and a total edge labelling function Definition 3 (Morphism, inclusion and rule) A graph morphism consists of a node mapping and an edge mapping that preserve sources, targets and labels: and 34 Adam Bakewell et al.

Morgan Kaufmann, 1999. [13] M. M. Gala. Web log analysis by applying graph transformation on semistructured temporal data. Sc. thesis, Politecnico di Milano, 2003. [14] R. Heckel and G. Engels. Graph transformation and visual modeling techniques. Bulletin of EATCS, 71:186–202, June 2000. [15] C. S. Jensen, C. E. Dyreson, and M. H. Bohlen et al. The consensus glossary of temporal database concepts - february 1998 version. In Temporal Databases: Research and Practice. (the book grow out of a Dagstuhl Seminar, June 23-27, 1997), volume 1399 of Lecture Notes in Computer Science, pages 367–405.

The suitability of general-purpose specification languages like OCL for specifying and checking shapes is unclear. PGRSs can define shapes with sharing and cycles. Our second example presents cyclic lists. Example 2 (Specification of cyclic lists) Fig. 2 gives rules defining cyclic lists. A single loop, is a cyclic list and all other cyclic lists reduce to Two-link cycles are reduced by TwoLoop. Longer cycles are reduced a link at a time by Unlink. Clearly a graph of several disjoint cycles will not reduce to a single loop; no rules reduce branching or merging structures, and acyclic chains cannot become loops.

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