Software Metrics and Object-Oriented Design Metrics

1. Major types of software metrics

Software metrics are quantitative measures used to understand and control software products, processes and projects. Four useful categories are:

Type	What it measures	Example
Product metrics	Characteristics of the software product	LOC, defect density, complexity
Process metrics	Effectiveness of the development/maintenance process	Defect removal efficiency, review effectiveness
Project metrics	Project progress and management	Effort, cost, schedule variance
Quality metrics	Quality attributes of the delivered software	Reliability, maintainability, usability, failure rate

2. Object-oriented design metrics

Object-oriented metrics quantify properties of classes, inheritance, coupling and cohesion. A well-known set is the CK (Chidamber–Kemerer) metric suite.

Important examples:

• WMC — Weighted Methods per Class: measures the number/complexity of methods in a class.
• DIT — Depth of Inheritance Tree: measures how deep a class is in the inheritance hierarchy.
• NOC — Number of Children: counts immediate subclasses of a class.
• CBO — Coupling Between Object classes: measures coupling between classes.
• RFC — Response for a Class: counts methods that can potentially execute in response to a message to the class.
• LCOM — Lack of Cohesion of Methods: indicates how unrelated the methods of a class are.

3. Quantitative assessment of quality

These metrics can be collected across versions and compared with thresholds or historical baselines.

For example:

• High CBO may indicate excessive coupling and lower maintainability.
• High LCOM may indicate poor class cohesion.
• Very high WMC may indicate a class that is difficult to understand or test.
• Large DIT can increase reuse but may also make behavior harder to understand.
• High NOC can indicate significant reuse of a superclass, but changes to the superclass may affect many subclasses.

Thus, object-oriented design metrics turn design characteristics into measurable indicators that can support quantitative quality assessment and identify classes needing refactoring or review.