We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity.
Abstract. In modern Integrated Development Environments (IDEs), textual editors are interactive and can handle intermediate, incomplete, or otherwise erroneous texts while still providing editor services such as syntax highlighting, error marking, outline views, and hover help. In this paper, we present an approach for the robust synchronization of interactive textual and graphical editors. The approach recovers from errors during parsing and text-to-model synchronization, preserves textual and graphical layout in the presence of erroneous texts and models, and provides synchronized editor services such as selection sharing and navigation between editors. It was implemented for synchronizing textual editors generated by the Spoofax language workbench and graphical editors generated by the Graphical Modeling Framework.
Recently graph has been drawing lots of attention both as a natural data model that captures fine-grained relationships between data entities and as a tool for powerful data analysis that considers such relationships. In this paper, we present a new graph database system that integrates a robust graph storage with an efficient graph analytics engine. Primarily, our system adopts two domain-specific languages (DSLs), one for describing graph analysis algorithms and the other for graph pattern matching queries. Compared to the API-based approaches in conventional graph processing systems, the DSL-based approach provides users with more flexible and intuitive ways of expressing algorithms and queries. Moreover, the DSL-based approach has significant performance benefits as well, (1) by skipping (remote) API invocation overhead and (2) by applying high-level optimization from the compiler.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.