Program Complexity Analysis Questions
Some metrics used to measure program complexity include:
1. Cyclomatic Complexity: This metric measures the number of independent paths through a program. It helps in identifying the complexity of control flow and the number of test cases required for adequate coverage.
2. Halstead Complexity Measures: These measures are based on the number of unique operators and operands used in a program. They provide insights into the program's volume, difficulty, and effort required for development.
3. Lines of Code (LOC): This metric simply counts the number of lines in a program. While it is a basic measure, it can give an indication of the program's size and potential complexity.
4. Maintainability Index: This metric combines various factors like cyclomatic complexity, lines of code, and code duplication to provide an overall measure of how maintainable a program is. It helps in assessing the ease of understanding, modifying, and debugging the code.
5. Fan-in and Fan-out: Fan-in measures the number of functions or modules that call a particular function or module, while fan-out measures the number of functions or modules called by a particular function or module. These metrics help in understanding the complexity of dependencies and potential impact of changes.
6. Depth of Inheritance Tree (DIT): This metric measures the number of levels in the inheritance hierarchy of a program. It indicates the complexity of class relationships and potential impact of changes.
7. Coupling and Cohesion: Coupling measures the degree of interdependence between modules or components, while cohesion measures the degree to which a module or component focuses on a single task. These metrics help in understanding the complexity of interactions and the potential for side effects.
It is important to note that these metrics should be used in combination and interpreted in the context of the specific program and its requirements.