Abstract

Conflict and dependency analysis (CDA) is a static analysis for the detection of conflicting and dependent rule applications in a graph transformation system. The state-of-the-art CDA technique, critical pair analysis, provides all potential conflicts and dependencies in minimal context as critical pairs, for each pair of rules. Yet, critical pairs can be hard to understand; users are mainly interested in core information about conflicts and dependencies occurring in various combinations. In this paper, we present an approach to conflicts and dependencies in graph transformation systems based on two dimensions of granularity. The first dimension refers to the overlap considered between the rules of a given rule pair; the second one refers to the represented amount of context information about transformations in which the conflicts occur. We introduce a variety of new conflict notions, in particular, conflict atoms, conflict reasons, and minimal conflict reasons, relate them to the existing conflict notions of critical pairs and initial conflicts, and position all of these notions within our granularity approach. Finally, we introduce dual concepts for dependency analysis. As we discuss in a running example, our approach paves the way for an improved CDA technique.

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