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entered) and the logical files (internal data storage) and the output and query functions that retrieve data stored from the internal stores and the external stores, interface files Note that these relationships have only been found to be relevant to software that operates as a self-contained system, that is, a cohesive set of functionality that is loosely coupled with other applications Therefore, it may not be advisable to use approximation-sizing techniques to predict the size of any enhancement project that has a mix of added, changed, and deleted functionality scattered over several functional areas within an application Figure 5-1 shows the relationships between the five components of the IFPUG functional size method from new development project data in the ISBSG Repository These relationships can be used to estimate the size of a project For projects sized by the IFPUG functional sizing method, versions 4x, and with an ISBSG quality rating of A or B, the relative contribution of each component type to the total count is depicted in Figure 5-1 Use these relationships to approximate the size of a software development project: If the high-level logical data model had 40 logical tables, it may be reasonably assumed that these relate to approximately 40 internal logical files Analysis of the ISBSG Repository also shows that most internal logical files in applications are rated as being low to medium in complexity The mean score attributed to them across all projects is 86 function points Based upon the preceding, it can be assumed that the total score for the internal logical files component of the function point count will be 40 (ILFs) 86 (mean score for internal logical files) = 344 FPs
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Example 1: Internal Logical Files
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External Queries 17% External Outputs 23%
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Internal Logical Files 25% External Inputs 27%
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External Interface Files 8%
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Figure 5-1 Function point mix new developments (Source: Estimating, Benchmarking & Research Suite Release 11)
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From the preceding pie chart it can be seen that the internal logical files component of the function point count is typically around 25 percent Based on this, the total functional size of the required application is predicted to be around: 344 FPs 100/25 = 1,376 FPs It would be sensible to notify the customer that the size is 1,400 FP (with an allowance of plus or minus 25 percent) In a situation where the planned project is a redevelopment of an existing application, the number of unique reports and extract files output from the existing application can be assumed to be equivalent to the external output components in the new project Analysis of the ISBSG Repository shows that most external outputs are rated as being medium in complexity The mean score attributed to them across all projects in the repository is 54 function points If the existing application has 47 different reports and 3 different extract files, then the total number of external outputs can be assumed to be 50 (Note: ensure that you exclude any obsolete, unused reports from your calculations) Based upon the preceding, it can be assumed that the total score for the external outputs component of the functional size measure will be 50 (EOs) 54 (mean score for external outputs) = 270 FPs From the pie chart in Figure 5-1, it can be seen that the external outputs component of the functional size measure is typically around 23 percent On this basis the total functional size for the required application is predicted to be around: 270 FPs 100/23 = 1,174 FPs It would be sensible to notify the customer that the size is 1,200 FP (with an allowance of plus or minus 25 percent)
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