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The Use of Complexity Metrics Throughout the Software Lifecycle

In: Computing Science and Statistics

Author

Listed:
  • Sallie Henry

    (Virginia Tech, Computer Science Department)

  • Steve Wake

    (Virginia Tech, Computer Science Department)

  • Wei Li

    (Virginia Tech, Computer Science Department)

Abstract

Software metrics attempt to uncover difficult or complex components of a software system. The hypothesis is that complex components are more difficult to understand, hence they are hard to maintain and more prone to error. Discovery of these complex components can aid the software developer in 1) selection of which components to redesign, 2) direct the testing effort and 3) give an indication of the maintenance effort required. Previous studies have demonstrated two main concepts. First, there exists a high correlation between design complexity and source code complexity. Secondly, metrics applied to source code have a high correlation to the maintenance activity needed. The results of this previous research motivates us to develop a methodology which uses complexity metrics throughout the software life cycle. Programmer productivity may be increased and software development cost may be reduced if error prone software is discovered early in the life cycle.

Suggested Citation

  • Sallie Henry & Steve Wake & Wei Li, 1992. "The Use of Complexity Metrics Throughout the Software Lifecycle," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 259-265, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_33
    DOI: 10.1007/978-1-4612-2856-1_33
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