Indirectly predicting the maintenance effort of open‐source software

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Abstract
An accurate maintenance effort model is essential for a successful software maintenance process. Maintenance effort is usually measured in person‐hours used to perform a maintenance task. However, maintenance effort data are usually only available for strictly managed software, such as closed‐source software. In other software projects that do not have complete maintenance records, especially some open‐source software, there are no direct data for maintenance effort, which precludes the establishment of a maintenance effort model. In this paper, we report a series of studies aimed at presenting a method for indirectly predicting the maintenance effort of open‐source software. This report covers two parts of our research. First, we examine the maintenance data from NASA SEL closed‐source software projects and identify some software measures that can be used to indirectly represent maintenance effort. Second, based on the findings in the first part, we analyze 121 recent versions of Linux, and use linear regression to construct two indirect maintenance effort models for the Linux project. Our study demonstrates the applicability of this approach to indirectly predicting the maintenance effort and improving the software maintenance process. Copyright © 2006 John Wiley & Sons, Ltd.

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