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A Proposal for Analysis and Prediction for Software Projects using In-Process Measurements and Collaborative Filtering of a Benchmarks Database

This paper proposes a new method for developing predictions and estimates for ongoing projects by comparing in-process measurements of the current project with benchmark data from previous projects. The method uses collaborative filtering to identify groups of similar projects in the benchmark database and then to develop predictions and estimates based on the in-process measurements of the current project and the comparison data from the similar projects. The authors base this proposal on experiments with multidimensional in-process project measurement in a middle-scale multi-vendor development project that lacked transparency in its processes.