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<p>Using data collected throughout a major project, the authors apply common statistical methods to quantitatively assess and evaluate improvements in a large contractor's software-maintenance process. Results show where improvements are needed; examining the change in statistical results lets you quantitatively evaluate the effectiveness of the improvements. We selected a process-assessment methodology developed by J.E. Henry (1993) that follows Total Quality Management principles and is based on Watts Humphrey's Process Maturity Framework. It lets you use a process modeling technique based on control-flow diagrams to define an organization's maintenance process. After collecting process and product data throughout the maintenance process, you analyze it using parametric and nonparametric statistical techniques. The statistical-analysis results and the process model help you assess and guide improvements in the organization's maintenance process. The method uses common statistical tests to quantify relationships among maintenance activities and process and product characteristics. The relationships, in turn, tell you more about the maintenance process and how requirements changes affect the product.</p>
software maintenance; software quality; electricity supply industry; statistical analysis; software maintenance; Martin Marietta; statistical methods; large contractor; software-maintenance process; statistical results; process-assessment methodology; Process Maturity Framework; process modeling technique; control-flow diagrams; nonparametric statistical techniques; parametric statistical techniques; requirements changes

J. Henry, S. Henry, D. Kafura and L. Matheson, "Improving Software Maintenance at Martin Marietta," in IEEE Software, vol. 11, no. , pp. 67-75, 1994.
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