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The regression equations based upon the combination of functional size and maximum team size allow the project estimates to be tuned in a manner that investigates the relationship between project effort and project duration These equations are best used in conjunction with the regression equations based upon functional size alone This is because, if used with unrealistic or unachievable maximum team size values, or without some knowledge of the likely relationship between project effort and project duration, the regression equations based upon the combination of values may generate unachievable and unacceptable project delivery rate and work effort estimates
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By utilizing the regression equations, Jenny has been able to quickly obtain indicative project effort and duration estimates for the SSRM project She might use such initial estimates to establish project feasibility She could decide that she is satisfied with these estimates and finish the analysis at this point Alternatively, she could decide to fine-tune the estimates to address additional specific project attributes that so far have not been explicitly considered Because Jenny feels that the SSRM project has some other specific attributes that are likely to impact the total project work and duration, but that have not been explicitly addressed by the regression equations, she decides to fine-tune her estimates based upon the ISBSG Repository data The following sections outline how she does this
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Example 2: Estimating Using Comparison
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The most obvious limitation of using regression equations to estimate project work effort and duration is that the equations fail to address many specific project attributes that are known to impact work effort and duration Although the provision of separate sets of regression equations for different development platforms improves this situation, the project delivery rate for an application developed using Lotus Notes is still likely to differ significantly from one developed using Java, even when they are both developed for the same midrange platform A further limitation of the regression equations as they were presented in the previous section is that they only provide a single value for each of the project estimates when, in many cases, a range of values would be more useful Having a range of estimate values allows the project manager to consider both optimistic and conservative as well as likely estimates when devising or validating the project schedule and budget The estimating by comparison technique presented here addresses both these limitations of regression equation based estimating by considering various specific project attributes and by generating a range of values for each of the project estimates
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project estimation Using the ISBSG repository
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The estimating by comparison technique begins by calculating optimistic, likely, and conservative project delivery rate and speed of delivery values for selections of projects from the ISBSG Repository that match the target project on a single attribute The averages of the project delivery rates and speeds of delivery for all the selections are then calculated, and these values are combined with the target project s functional size to generate optimistic, likely, and conservative estimates for the target project s work effort and duration The estimating by comparison technique is described in detail in the following section
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The Estimating by Comparison Technique
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Estimating by comparison utilizes the following approach to estimate project work effort and duration using data from the ISBSG Repository: 1 For the target project, determine its functional size and identify its project type and development platform 2 Use the target project s functional size and development type and platform to select a subset of similar projects from the ISBSG Repository5 Estimates generated by the estimating by comparison technique will only consider the selected subset of projects The functional size used to select projects from the ISBSG Repository is expressed as a range of sizes rather than as a single value The estimator may choose not to restrict the set of projects for consideration based upon one or a selection of functional size and development type and platform The reason for restricting the projects for selection in this way, however, is that analysis of the ISBSG Repository has shown that each of functional size, development type, and development platform has significant impact upon project work effort and duration Restricting the estimating by comparison technique to consider only those projects of a similar functional size, and having the same development type and platform as the target project, should therefore provide more accurate estimates than simply considering all the projects in the repository 3 For each of the target project s attributes recorded in the ISBSG Repository, calculate the optimistic, likely, and conservative
The complete ISBSG project data is available on the ISBSG Estimating, Benchmarking & Research Suite ISBSG also provides the ISBSG Comparative Estimating tool Both these products can be licensed from wwwisbsgorg or from ISBSG member organizations
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