Size-Oriented vs. Function-Oriented Metrics

Software metrics can be categorized into Size-Oriented Metrics and Function-Oriented Metrics, both of which measure software productivity and quality but use different approaches. Below is a detailed comparison between the two types.

1. Size-Oriented Metrics

Size-oriented metrics measure software based on physical size, such as lines of code (LOC), the number of modules, or delivered bytes. These metrics assume that larger software requires more effort to develop and maintain.

Key Characteristics

✅ Based on size (e.g., lines of code, number of modules).
✅ Easier to measure since LOC is directly countable.
✅ Good for comparing projects of similar technology.
✅ Works well for procedural languages like C, Java, and Python.
❌ Not ideal for object-oriented and high-level languages (e.g., SQL, UML).
❌ Doesn’t account for complexity or efficiency.

Common Size-Oriented Metrics

2. Function-Oriented Metrics

Function-oriented metrics measure software based on functionality delivered to the user instead of size. This approach focuses on what the software does rather than how many lines it has.

Key Characteristics

✅ Based on function points (FP), not lines of code.
✅ More useful for high-level languages and modern software (e.g., web apps, AI, cloud computing).
✅ Considers complexity and user functionality.
✅ Better for comparing projects across different technologies.
❌ Harder to calculate compared to LOC.
❌ Requires expert judgment for accurate measurement.

Common Function-Oriented Metrics

Comparison Table: Size-Oriented vs. Function-Oriented Metrics

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