Subscribe by Email

Friday, August 5, 2011

What are different component level design metrics?

Component level design focuses on internal workings of software and include measures: cohesion, coupling, and complexity. It helps in judging the quality of a component level design. Once a procedural design is developed, component level design metrics can be applied. It is possible to compute measures of the functional independence, coupling and cohesion of a component and to use these to assess the quality of design.

The cohesiveness of a module can be described by a set of metrics:
- Data slice which is defined as a backward walk that searches for data values that can affect the state of the module.
- Data tokens are variables defined for a module.
- Glue tokens are set of data tokens on data slice.
- Superglue tokens are data tokens common to every data slice in a module.
- Stickiness of glue token is directly proportional to number of data slices it binds.

Coupling metrics is an indication of connectedness of a module to other modules. The metric for module coupling encompasses data and control flow coupling, global coupling and environmental coupling.

Complexity metrics are used to predict critical information about the reliability and maintainability of software systems from automatic analysis of source code. It also provides feedback during software project to help control the design activity. Cyclomatic complexity is the most widely used complexity metric.

1 comment:

anandhi said...

Thank you for posting such a useful, impressive and a wicked article./Wow.. looking good!
Software Testing Tutorial

Facebook activity