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 precise specification of software models is a major concern in model-driven design of object-oriented software. In this paper, we investigate how program graphs, a language-independent model of object-oriented programs, can be specified precisely, with a focus on static structure rather than behavior. Graph grammars are a natural candidate for specifying the structure of a class of graphs. However, neither star grammars—which are equivalent to the well-known hyperedge replacement grammars—nor the recently proposed adaptive star grammars allow all relevant properties of program graphs to be specified. So we extend adaptive star rules by positive and negative application conditions, and show that the resulting conditional adaptive star grammars are powerful enough to generate program graphs. 1