Information Flow Metrics
Information Flow Metrics are used to measure software complexity based on how components interact and exchange data within a system. The concept is based on the idea that the simplest system is composed of components, and the system’s complexity is determined by the work these components perform and how they are connected.
Key Definitions
- Component: Any element obtained by breaking down a software system into its constituent parts.
- Cohesion: The degree to which a component performs a single, well-defined function.
- Coupling: The degree of linkage between one component and other components in the system.
About Information Flow Metrics
- Introduced by Henry and Kafura, these metrics are sometimes called Henry and Kafura’s Metric.
- They assess complexity by observing information flow among system modules.
- The measure considers both:
1. Complexity of the procedure code itself (measured using LOC – Lines of Code).
2.Complexity from the procedure’s connections to its environment (measured using FAN-IN and FAN-OUT).
Key Terms
- FAN-IN: The number of local flows into a procedure plus the number of data structures from which the procedure retrieves information.
- FAN-OUT: The number of local flows from a procedure plus the number of data structures that the procedure updates.
Formula for Procedure Complexity
Procedure Complexity=Length×(FAN-IN×FAN-OUT)^2
Where:
- Length = Size of the procedure (in LOC).
- FAN-IN and FAN-OUT represent data and control flow connections.
