Abstract
The planning of software maintenance is a major problem that information systems managers are facing in many organizations. The problem stems from two basic root causes: the competing demands (services, repairs, improvements, etc.) for the same limited maintenance resources and the uncertainty associated with these demands. Managers lack reliable tools that could enable them to handle the uncertainty and thereby proactively plan the maintenance to better respond to user requests. This study provides a quantitative method to estimate the uncertainty and to help managers forecast the demands of maintenance. Since the accuracy of maintenance request forecast depends on predictable regimes of demands, the method first hypothesizes a non-stationary, life-cycle model for the basic regimes of different types of maintenance requests. Each regime features a probabilistic dominance of certain types of requests in the overall distribution of demands. The method then includes ways to characterize the distributions of different types of requests, monitor their evolution, and determine the shifting of regimes on which the managers base their planning decisions. This study performs a laboratory experiment to validate the quantitative method that determines the software maintenance life cycle. The findings confirm the hypothesis and substantiate the appropriateness of the quantitative method proposed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.