
Function-Oriented Metrics are software measurement techniques that evaluate software size and complexity based on the functionality delivered to the user , rather than the physical code size.
Function-Oriented Metrics are software measurement techniques that evaluate software size and complexity based on the functionality delivered to the user, rather than the physical code size.
π In simple words: They measure what the software does, not how many lines of code it has.
Unlike size-oriented metrics (LOC-based), function-oriented metrics focus on:
π So they are user-centric metrics.
Function Points measure software size based on the functional requirements provided to the user.
Function Points are calculated using 5 components:
FP = Total Unadjusted Function Points Γ Value Adjustment Factor (VAF)
UFP = Sum of all weighted EI, EO, EQ, ILF, EIF
VAF = 0.65 + (0.01 Γ Ξ£Fi)
π Fi = 14 general system characteristics (like performance, complexity, security)
| Component | Count |
|---|---|
| Inputs | 5 |
| Outputs | 4 |
| Queries | 3 |
| Files | 2 |
| Interfaces | 1 |
π These are converted into weights β FP is calculated.
β Language independent β Focus on user requirements β Better for business applications β Useful in early project estimation β More accurate than LOC-based metrics
| Feature | Function-Oriented | Size-Oriented |
|---|---|---|
| Basis | Functionality | Lines of Code |
| Unit | Function Points | LOC |
| Language dependence | No | Yes |
| Focus | User requirements | Code size |
| Accuracy | Higher | Lower |
Function-oriented metrics measure software size based on the functionality delivered to the user. The most common method is Function Point Analysis, which considers inputs, outputs, inquiries, files, and interfaces to estimate software size and effort.
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