Improved size and effort estimation models for software maintenance

UnrestrictedAccurately estimating the cost of software projects is one of the most desired capabilities in software development organizations. Accurate cost estimates not only help the customer make successful investments but also assist the software project manager in coming up with appropriate plans for the project and making reasonable decisions during the project execution. Although there have been reports that software maintenance accounts for the majority of the software total cost, the software estimation research has focused considerably on new development and much less on maintenance.; In this dissertation, an extension to the well-known model for software estimation, COCOMO II, is introduced for better determining the size of maintained software and improving the effort estimation accuracy of software maintenance. While COCOMO II emphasizes the cost estimation of software development, the extension captures various characteristics of software maintenance through a number of enhancements to the COCOMO II size and effort estimation models to support the cost estimation of software maintenance.; Expert input and an industry data set of eighty completed software maintenance projects from three software organizations were used to build the model. A number of models were derived through various calibration approaches, and these models were then evaluated using the industry data set. The full model, which was derived through the Bayesian analysis, yields effort estimates within 30% of the actuals 51% of the time, outperforming the original COCOMO II model when it was used to estimate these projects by 34%. Further performance improvement was obtained when calibrating the full model to each individual program, generating effort estimates within 30% of the actuals 80% of the time