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Benefits of Measuring Software through Cyclomatic Complexity

A proverb in the IT world says that if you can’t measure something, there is no way you can manage it. Understanding the complexity of an organization’s application portfolio offers insight into how it can be managed best. The biggest problem is that the things that make up software complexity – overwritten and rewritten code, legacy system remnants, etc. – are the very same things that make measuring it a feat.

In some cases, with so many system interfaces and compound requirements, the complexity of software systems can spiral out of control, leading to soaring costs and risks. Software complexity can thrive in completed projects if left unchecked, and the result are bloated, unmanageable applications. Experts would even say that the act of maintaining software itself comes with some extent of degradation.

Complexity Metrics

Fortunately, there have been a lot of methods created to measure software complexity, and among the most widely used is cyclomatic complexity, which measures the amount of control flow in a program. Programs that operate with more conditional logic are harder to understand, and measuring its level of cyclomatic complexity reveals how much has to be managed.

Using cyclomatic complexity on its own can bring incorrect results, however. Even if a module is complex, it doesn’t necessarily have lots of interactions with modules outside. A module may be comparatively simple too, and yet it can be highly coupled with a lot of other modules, which then increases the full complexity of the codebase to a substantial extent. Complexity metrics will be bad in the first scenario. In the second, they will look good, but the result will be inaccurate. It is thus crucial for the coupling and cohesion of the modules in the codebase to be measured too so get a true system-level, software complexity measure.

Organizations with this information can gain from it in several number ways, the following being the top five:

More Predictability

By knowing the level of complexity of the code, it becomes easier to know how much maintenance will be required for a program.

Software Risk Control

Software complexity management reduces the chances of issues being introduced into production.

Less Cost

It is important to be proactive when preventing excessive or unnecessary software complexity as this lessens maintenance costs when an organization is ready for eventualities.

Added Value

As seen in past years, too complex applications lead to issues. By controlling complexity, organizations can preserve the value of their software assets as well as sustain their utility.

Decision Support

There are codes that are so complex that they’re just not worth saving. Proving the costs of a rewrite, it can be decided whether existing code must be kept or a new code must be written altogether.

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