Product News
Oakland, CA, May 7, 2010—Tom Sawyer Software, the leading provider of high-performance graph visualization, layout, and analysis solutions, announces the release of Tom Sawyer Analysis, Version 8.0, C++ Edition.
Tom Sawyer Analysis delivers sophisticated component technology that enables software developers to simplify and automate the analysis of complex systems found in applications ranging from life sciences to networking and intelligence.
Tom Sawyer Analysis, C++ Edition lets developers integrate algorithmic analysis within their applications and perform highly sophisticated analytic queries on relational information models. The software facilitates clustering, structured graph traversal, dependency analysis, network flow analysis, impact analysis, cycle detection, process analysis, and other complex queries on relational models.
Tom Sawyer Analysis, Version 8.0, C++ Edition adds support for Microsoft Visual Studio 2008 and 64-bit computers. It allows users to stay on top of the latest technology and develop with the newest features and functionalities of Microsoft Visual Studio 2008. Further, users are able to improve the performance and scalability of their applications with 64-bit support. This release also improves the All Pairs Shortest Paths, Shortest Paths, and Tree Test algorithms.
Tom Sawyer Analysis, Version 8.0, C++ Edition, offers new and enhanced features:
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Documentation
Tom Sawyer Software is the leading provider of software and services that enable organizations to build highly scalable and flexible graph and data visualization and analysis applications. These applications are used to discover hidden patterns, complex relationships, and key trends in large and diverse datasets. Tom Sawyer Software serves clients with needs in link analysis; network topology; architectures and models; schematics and maps; and dependencies, flows, and processes. We help clients federate and integrate their data from multiple sources and build the graph and data visualization applications that are critical to analyzing and gaining insight into their data.
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