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Software project estimation Framework
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hours less effort per function point produced than is typical for all projects However, if the example project team used only one- to fourperson teams on its Visual Basic PC projects, adjusting the median PDR down by 51 hours per function point would result in a PDR of 21 hours per function point This is close to the productivity of the best VB projects in the ISBSG database, which is likely to be unachievable In this situation, our example development team would be better off making a more conservative adjustment to the PDRs for smaller team sizes, such as the P75 value of 21 Examining Table B-45 shows that a team of five to eight on a project of more than 1,000 FPs is unusual Only 4 of the 1,681 projects had such a small team on a project of that scope This is too small a sample to provide usable statistics The PDR improvement values (that is, the negative values) in this table also show that this team size on large projects generally achieves high productivity However, once again you need to take care in selecting the PDR adjustment value For our example team, a value of 33 from the Max column seems appropriately conservative Using these figures will result in the following PDR table for the team
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Step 4 Benchmarking Your Projects PDR
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Without benchmarking your projects, you will find it difficult to use these PDR ranges extracted from the ISBSG tables The range of the PDRs present in Appendix B will likely be too wide for commercial acceptability You will need to benchmark whatever projects exist in your team s history, or to narrow the range arbitrarily To benchmark a few of your team s projects, perform the following steps: 1 Calculate each project s PDR, in hours per function point When doing this, consider the scope of activities included in the PDR The effort figure used for the calculation should cover the full development life cycle 2 Decide the development language and platform for each project This will determine the set of PDR distributions you will extract from Appendix B to use for benchmarking (Tables B-17, B-18, B-19, and B-20) Also identify the maximum team size for each project 3 Based on a project s language and team size, select the appropriate PDR distribution you have extracted from the ISBSG Our example team would compare the PDR for a fourperson project that used Java with the PDR distribution on the first row of Table 16-2 This will place the team s project within one of the quartiles of the PDR distributions Our example team s project had a PDR of 41 hours per FP, which places it in the P25-to-median quartile
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Min P10 33 25 19 P25 40 42 32 Median 43 65 51 P75 60 165 74 P90 97 347 117 Max 171 609 244
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Table 16-2
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Project Delivery Rates by Language for 1 4 Team Size
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4 Perform this comparison for each project PDR that you have available from the projects that your team has completed This is likely to reveal that most projects sit within the same quartile of the relevant row in the draft PDR table This is your team s benchmark quartile, and consequently provides a narrower range of PDR values for use in the estimating equation Benchmarking your team s projects against the ISBSG data will show that this data can provide only approximate PDR tables A team s own project history would produce much more accurate PDR tables
Step 5 Construct the Estimation Framework
After benchmarking one or more of your projects against the PDR distributions extracted from the ISBSG tables, you can construct the estimation framework Typically, you can create one PDR table that has Team Size across the columns and Languages down the rows In each table cell are the appropriate top and bottom PDR values from your group s benchmark quartile For our example development team, the estimating framework PDR table would be as shown in Table 16-3 When using these tables, remember that projects delivering under 400 function points typically have distinctly worse PDRs, and projects delivering more than 1,000 FPs typically have distinctly better PDRs The cause of this impact is unclear, but it probably relates to economies of scale Doing a larger amount of work as a coherent whole can typically proceed more efficiently than a smaller amount of work Remember that this impact of project size occurs after taking into account the impact of team size Because team size has such a large negative impact on productivity, it counters the beneficial impact of
Team Size 1 4 (<400FP Project) 36 43 42 65 32 51
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