Even though there are a number of software size and effort measurement methods proposed in literature, they are not widely adopted in the practice. According to literature, only 30% of software companies use measurement, mostly as a method for additional validation. In order to determine whether the objective metric approach can give results of the same quality or better than the estimates relying on work breakdown and expert judgment, we have validated several standard functional measurement and analysis methods (IFPUG, NESMA, Mark II, COSMIC, and use case points), on the selected set of small and medium size real-world web based projects at CMMI level 2. Evaluation performed in this paper provides objective justification and guidance for the use of a measurement-based estimation in these kinds of projects.

The use case point (UCP) method is one of the most commonly used size estimation methods in software development. Applicability of UCP size for the project effort estimation is thoroughly investigated; however, little attention is devoted to the effort estimation of particular task types. The authors have created and cross-compared prediction models for estimating task-type efforts by means of UCP size using an Online analytical processing model and R packages on a set of 32 real-world projects, with the goal of facilitating analysis of the correlation between project sizes and effort required to complete task types. Requirements, scoping, functional specification, and functional testing task types have up to two times better estimation accuracies than project effort. Implementation has slightly better accuracy than the project effort, while the other task types are not correlated to the UCP size. Using estimates of the most correlated task types and other techniques, such as expert judgment for others, we improved the overall project effort prediction accuracy and decreased the error from 26 to 16%.

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