We present new algorithms for labeling a set P of n points in the plane with labels that are aligned to one side of the bounding box of P . The points are connected to their labels by curves (leaders) that consist of two segments: a horizontal segment, and a second segment at a fixed angle with the first. Our algorithms find a collection of crossing-free leaders that minimizes the total number of bends, the total length, or any other 'badness' function of the leaders. A generalization to labels on two opposite sides of the bounding box of P is considered and an experimental evaluation of the performance is included.

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Introduction GrGen.NET is a graph rewrite tool enabling elegant and convenient development of graph transformation applications with comparable performance to manually developed ones. GrGen.NET compiles declarative specifications of graph meta models, patterns, and rewrite rules into .NET modules. The entire functionality (meta-model, matching, rewriting, elementary graph operations) is accessible through a convenient API (called libGr) enabling easy integration of GrGen.NET into custom applications. Meta-model and rule languages have formal semantics based on a new combination of category theory and denotational semantics [1].The general purpose graph rewrite tool GrGen.NET is a descendant of GrGen [2], initially developed for transformations in compiler construction [3]. GrGen.NET is published under LGPL along with a user manual.

Abstract. We present new algorithms for labeling a set P of n points in the plane with labels that are aligned to the left of the bounding box of P . The points are connected to their labels by curves (leaders) that consist of two segments: a horizontal segment, and a second segment at a fixed angle with the first. Our algorithm finds a collection of nonintersecting leaders that minimizes the total number of bends, the total length, or any other 'badness' function of the leaders. An experimental evaluation of the performance is included.

Abstract. With graph pattern matching the field of graph transformation (GT) includes an NP-complete subtask. But for real-life applications it is essential that graph pattern matching is performed as fast as possible. This challenge has been attacked by the approach of search plan driven, host-graph-sensitive (also known as model-sensitive) graph pattern matching. To our knowledge no experimental evaluation of this approach has been published yet. We performed first experiments regarding the runtime performance using the well-known GT benchmark introduced by Varró et al. as well as an example from compiler construction. Moreover we present an improved cost model and heuristics for search plans and their generation.