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Selecting a software size metric sets you down a specific track.

Deciding on which software size metric you should use is a fairly momentous decision. Much like deciding on a development platform the decision on which size measure will commit an organization to different types of tools, process and techniques. For example the processes and tools needed to count lines of code would be different than those needed to support story points as a sizing technique. The goals of the measurement program will be instrumental in the determining which type of size metrics will be the most useful. Measurement goals will help you choose between four macro attributes of organization specific and industry defined metrics and between physical and logical metrics. For example, if benchmarking against other firms or industry data is required to attain your measurement goal using organizationally defined metrics would be less viable. Similarly if you have a heterogeneous software environment then selecting a functional metric would make more sense than using a physical metric (logical metrics normalizes varied technology).

Figure 1:Balancing Organizational Perspective Versus Organizational Environment

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The second checkbox is whether the measure has an externally defined and documented methodology. Why is definition important? Definition is the precursor to repeatability and consistency, which allows comparability. Consistency and repeatability are prerequisites for the ability to generate data needed to use the scientific method such as Six Sigma and tools used to support Kiazen. Finally, an external definition reduces the amount of effort that is required to construct and implement measurement programs.

Even where a definition exists a wide range of nuances are possible. Examples of the range of definitions begin with the most defined, the functional precision of ISO functional metrics to the less defined methodology of Use Case Points which began with a single academic definition and has evolved into many functional variants. The variants seen in UCP are a reflection of having no central control point to control methods evolution, which we will explore later in this model. The range of formality of definition is captured in Figure 2.

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Figure 3 consolidates the view of formality of definition with the delineation between logical and physical metrics. Each measure has strengths and weaknesses. The first two items in our checklist are macro filters.

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Each measure of size fits a specific combination of organizational goals, environmental constraints and needs however the field of potential software sizing metrics is wide and varied. Once the macro filter is applied each subsequent step in the checklist will narrow the field of potential size measures.

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