A Procedure for Analyzing Unbalanced Datasets
IEEE Transactions on Software Engineering
Software Productivity Measurement Using Multiple Size Measures
IEEE Transactions on Software Engineering
Finding the Right Data for Software Cost Modeling
IEEE Software
Lessons learnt from the analysis of large-scale corporate databases
Proceedings of the 28th international conference on Software engineering
Evaluating the suitability of a measurement repository for statistical process control
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Measuring and predicting software productivity: A systematic map and review
Information and Software Technology
Do crosscutting concerns cause modularity problems?
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
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The authors demonstrate that the recommendations for analyzing productivity in the appendix to the ISO/IEC 15939 standard are inappropriate. They also show that problems with the ISO/IEC advice can be compounded if software engineers attempt to apply statistical process-control techniques to software productivity metrics. They recommend using small meaningful data sets as the basis for productivity analysis and using effort-estimation models to assess productivity rather than productivity metrics.This article is part of a special focus section on software metrics.