Function-Oriented Metrics uses the functionality of the software as the normalization value. We cannot measure the functionality of the software directly but it must be derived indirectly using other direct measures.
The concept of Function-Oriented Metrics is suggested by Albrecht who suggested a measure called the function point. While calculating function point five information domain values are considered.
- Number of user inputs
- Number of user outputs
- Number of user enquiries
- Number of files
- Number of external interfaces
To compute function points (FP), the following equation is used:
FP = count total *[0.65 + 0.01 * ?(Fi)]
Where count total is the sum of all FP entries and Fi (i = 1 to 14) is complexity adjustment values.Fi value is based on 14 question. I have not included these 14 questions here; you can get online help for these questions. Each of these questions is answered using a scale that ranges from 0 to 5. Not important-0, Incidental-1, Moderate-2, Average-3, Significant-4, Essencial-5
The concept of Function-Oriented Metrics is suggested by Albrecht who suggested a measure called the function point. While calculating function point five information domain values are considered.
- Number of user inputs
- Number of user outputs
- Number of user enquiries
- Number of files
- Number of external interfaces
To compute function points (FP), the following equation is used:
FP = count total *[0.65 + 0.01 * ?(Fi)]
Where count total is the sum of all FP entries and Fi (i = 1 to 14) is complexity adjustment values.Fi value is based on 14 question. I have not included these 14 questions here; you can get online help for these questions. Each of these questions is answered using a scale that ranges from 0 to 5. Not important-0, Incidental-1, Moderate-2, Average-3, Significant-4, Essencial-5
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