Author: Lam, Hoi-hing
Title: The economics of software maintenance cost model for software maintenance
Degree: M.Sc.
Year: 2000
Subject: Software maintenance
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Department of Computing
Pages: iv, 87 leaves : ill. ; 31 cm
Language: English
Abstract: While realized that almost two-third of all life-cycle costs are spent in the Operations and Maintenance phase of the software life cycle, it is worth to develop a cost estimation model tailored for the software maintenance. Current cost estimation models are reviewed and their applicability in software maintenance are examined. COCOMO 2.0, to be one of algorithmic cost estimation models best document, is selected to be the basis for the proposed new model SMA-COCOMO. Though the software maintenance environment is very similar to the development one, SMA-COCOMO has taken the specific characteristics of maintenance environment into account - there is very little functional requirements changes, relatively much stable platform environment and single maintenance center. SMA-COCOMO drops the source size adjustment factor of breakage percentage, and the two multiplicative cost drivers 'platform volatility' and 'multi-site development' while adding two cost drivers 'network constraint' and 'business experience' to captures the latest software technology trends. In SMA-COCOMO, there are relationships established from the rating of three cost drivers, 'platform experience', 'language and tool experience' and 'application experience' to other cost drivers. Two data groups, 'COCOMO Maintenance Project Database' and 'Y2K Problem Fixing Costs', are used to evaluate the SMA-COCOMO. Though it failed to prove that better cost estimation for software maintenance projects can be provided by SMA-COCOMO, SMA-COCOMO provides a useful framework which provides better view on the software maintenance and it acts as a base for further study on software maintenance. However, the usefulness of SMA-COCOMO is depended on further calibration of the different cost drivers' effort multiplier and this will rely heavily on the size and quality of the maintenance project database.
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