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Scalable Techniques for Modeling Software Interconnectivity

In: Computing Science and Statistics

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  • Richard W. Selby

    (University of California, Department of Information and Computer Science)

Abstract

Software systems contain multiple types of interrelations among components — data, control, and sequencing, among others. We are developing interconnectivity analysis techniques that derive multiple views of the structure of large-scale software systems. These techniques calculate interconnections among components and then recursively group the components into sets according to their degree of interconnection. These techniques are especially suited to large-scale systems (e.g., > 100,000 lines) since numerous types of interconnections can be determined automatically in a tractable manner. Interconnectivity analysis techniques produce visualizations of system structure and can be used to document systems, model their evolution over time, compare system structure, guide regression testing, or localize error-prone structure. In earlier work, one such technique was applied effectively in a feasibility study to characterize the error-prone components in a large-scale system from a production environment. Tools supporting interconnectivity analysis will be integrated into the Amadeus measurement-driven analysis and feedback system.

Suggested Citation

  • Richard W. Selby, 1992. "Scalable Techniques for Modeling Software Interconnectivity," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 249-258, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_32
    DOI: 10.1007/978-1-4612-2856-1_32
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