Graphs are used as models in all areas of computer science: examples are state space graphs, control flow graphs, syntax graphs, UML-type models of all kinds, network layouts, social networks, dependency graphs, and so forth. Used to model a particular phenomenon or process, graphs are then typically analyzed to find out properties of the modelled subject, or transformed to construct other types of models.
Graphs as Models combines the strengths of two pre-existing workshop series: GT-VMT (Graph Transformation and Visual Modelling Techniques) and GRAPHITE(Graph Inspection and Traversal Engineering), but also solicits research from other related areas, such as Social Network Analysis.
Graphs as Models is a satellite workshop of ETAPS 2015.
This workshop seeks to attract and stimulate research on the techniques for graph analysis, inspection and transformation, on a general level rather than in any specific domain. Thus, the concept of a graph (in its many guises) is central; contributions should address scenarios for the use of graphs in a modelling context that potentially transcend specific settings and can be applied across domains. Good, well-known examples of such techniques are model checking and graph transformation; but we welcome contributions on any of the following (non-exhaustive) list of topics:
- The use of graphs in software development, such as synthesis, planning, bug mitigation and repair
- The use of graphs in software analysis, such as verification, testing, static analysis, and simulation
- Graph search optimization techniques such as state space reduction techniques and search heuristics
- Graph algorithms exploiting parallel and distributed architectures, such as clusters, grids and cloud platforms
- Graph algorithms exploiting dedicated hardware, such as graphics processing units and massive storage
- Dedicated algorithms or implementation techniques for graph matching, isomorphism checking, graph distance and other graph-based problems
- Stochastic processes on graphs, including random walks
- Analysis of large graphs, such as large state spaces, social network graphs, large networks, and big (graph) data
- Visual language definition and syntax, such as meta-modelling, grammars and graphical parsing
- Static and dynamic semantics of visual languages, including OCL, graph constraints, simulation and animation
- Model-to-model and model-to-text transformations and their application in model-driven development
- Visual modeling techniques and graph transformations for systems with quality properties like performance, real-time, safety, reliability, and energy consumption
- Case studies and applications
- Tool support for any of the above
This is a two-day workshop programmed as a mixture of:
- Submitted paper presentations
- Fully interactive sessions, such as:
- Community challenges: What open issues do you see? What unresolved, graph-related problems are you facing? Give a 5-minute presentation and receive 10 minutes of feedback and in-depth discussion from an involved audience
- Brainstorm groups: Be part of a small group for a 45-minute brainstorm discussion on a chosen topic concerning the use of graphs as models; think out of the box and bring back your conclusions afterwards
- Informal tool demos: Convince the audience in 10 minutes that they really need the functionality your graph-based tool offers