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Classifying Size Approximation Techniques
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Basically, any approximation technique comprises some input, calculation, and output, where the input variables are some kind of information about the software project being sized, and the basic output is the approximated size Size approximations may use a direct or derived approach: Direct size approximation ( expert opinion ) predicts the size based on analogical reasoning and intuition, typically using past experience; the size result is achieved directly without a formal step-by-step, structured process Direct estimation may be improved by means of Delphi iterations7 or some kind of analogy with known projects Derived size approximation ( algorithmic method ) involves a defined algorithmic or structured approach, based on theoretical or statistical models
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Here we look at the accuracy of the sizing approximations provided in the projects submitted to the ISBSG repository when compared with the counted size of the software delivered
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In 3 we saw that 30 to 40 percent of projects used functional size techniques as part of estimating duration, effort, or cost They may have used an approximation of size, or a size value counted carefully from the project specification; the latter is perhaps most likely This section considers a different question: if size in function points was approximated early in a project, how does the approximation compare with the final properly counted size Errors can arise from several sources: inaccuracies that are inevitable when an approximation is produced from incomplete information; inaccuracies that might be caused by using a poor technique to do the approximation; and scope creep, when the final system contains functionality that was not part of the initial specification Three main techniques are used for approximating size: 40 percent approximate size from a data model 20 percent approximate size from the functional specification or use case model 16 percent approximate size by analogy with previous projects Generally, size is approximated well Perhaps this is to be expected in a database of projects primarily submitted by organizations that establish size by some form of functional sizing method Size approximations are provided for 322 projects: 12 percent over-approximated size by at least 10 percent; 8 percent over-approximated size by at least 20 percent 53 percent were approximated accurately to within 10 percent (16 percent were exact); 65 percent were estimated accurately to within 20 percent 35 percent under-approximated size by at least 10 percent; 27 percent underestimated size by at least 20 percent The proportional size of these groups is about 1 (over-approximate) to 6 (accurate) to 3 (under-approximate) There is a slight indication that errors are larger when approximation is based on a data model rather than on the functional specification or use case model, but really the pattern varies little whichever methods are used When size is over-approximated, the average error is about 30 percent When it is under-approximated by 10 percent or more, the median under-approximation is 30 percent; among projects where the under-approximation is 20 percent or more, the median underapproximation is 60 percent The largest error is nearly 400 percent, meaning the actual size was almost five times the approximation
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In summary, for over half of the projects the size approximation is accurate Of the rest, under-approximations are about three times as likely to occur as over-approximations, and the error is likely to be two or more times as bad Approximations produced from the functional specification are slightly more likely to be more accurate than those produced from a data model
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Summary
In this chapter we have introduced the concept that functional size measurement of software can be performed at different levels of accuracy to suit different purposes, and we have provided a six-level accuracy hierarchy We have also introduced the concept of approximating size rather than measuring size and have looked at the accuracy of the approximations submitted to the ISBSG Repository
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