In layman’s terms, everything in the world can be measured by how complex it is; baking a cake, composing a piece of music or writing a blog article ;-), but an important aspect to note is that whether something is highly complex or less complex doesn’t necessarily reflect on if it is good or bad. Some of the greatest recipes in the world only include 3 or 4 ingredients, but similarly you can create a highly complex meal using 50 ingredients, you don’t judge the end product by it’s complexity but rather use the level of complexity to guide you in understanding how easy it is to create, replicate or maintain standards in its production.
For Code Complexity the exact same reasoning can be applied. Whatever method for tracking Code Complexity is being used, the outcome of the complexity score should only ever be used to guide decision making and strategy, it won’t ever be a ‘right or wrong’ style output.
In software development, “code complexity” is used as a critical measure, often aiming to provide insights into the maintainability, understandability, and potential vulnerabilities of code. In the following article we aim to explain what code complexity means, explore the various methods for measuring it, and explain its significance in software engineering. We’ll conclude with a look at why Cyclomatic Complexity, a particular measure of code complexity, is preferred by experts, including us at The Code Registry, for ensuring software quality and security.
What is Code Complexity?
First up, lets get into what Code Complexity actually is and what it measures.
Code complexity is a quantitative assessment of how complicated a piece of code is, simple right?. It’s an essential concept in software development, as it directly impacts the effort needed for code maintenance, testing, and understanding. Generally speaking, the higher the complexity score is, will often indicate how difficult the code will be to work with, potentially leading to errors, bugs, and security vulnerabilities. On the flip side, a lower complexity score suggests that the code is more straightforward, easier to manage, and less prone to issues. As mentioned above though, these are very general assessments, for some code bases there may be very good reasons for the Code Complexity score to be on the high side or for it to be unavoidable due to the nature of the software being developed. That being said, regardless of the reasons, a high code complexity score is a very strong indication that you, as the business leader, will need to expect that your code won’t be fast to develop or easy for junior developers to work on. For business or technical leaders, the benefits of measuring and reducing their code complexity includes;
- Being able to evaluate the risks associated with the program.
- Identify overly complex logic or insufficient modularity in your code, to guide future development improvements
- Assess ways to achieve better maintainability
- Identify and reduced defects
- Include within enhanced testing
- Ultimately a reduced complexity will lead to improved productivity.
As we’ve already said, some code needs to be more complicated of course. But with Code Complexity scoring and tracking what you want to be looking for is code that’s unnecessarily complex that can be improved to provide the benefits listed out above.
Code Complexity Methods
So, how do you measure it? Luckily over the years there have been several methods and metrics developed that can help measure code complexity and help you identify potential areas for improvement within the codebase, below we dive into a few of these methods.
Cyclomatic Complexity:
Originally Cyclomatic Complexity was a measurement developed by Thomas McCabe to determine the stability and level of confidence in a program. It measured the number of linearly-independent paths through a program module, ultimately determining that programs with lower Cyclomatic Complexity were easier to understand and less risky to modify. This measure is particularly crucial for understanding the testing effort required in software development, as it directly correlates with the number of test cases needed to achieve complete path coverage. A Cyclomatic Complexity score will normally be expressed as a numerical figure between 1-10 whereby a score of ‘1’ is deemed very good with no or few overly complex paths and a score of 10 suggests there are significant areas of the code that could be reworked for the better.
Halstead Complexity Measures
Proposed by Maurice Halstead in 1977, these measures are based on the number of operators and operands (an object of a mathematical operation) in the code. Halstead’s metrics focus on the volume, difficulty, and effort to understand and maintain the code, providing insights into the potential errors and the overall complexity of a software module. In simple terms it refers to the measure of the amount of information in the source code. It counts the number of variables and how often they appear – meaning the more variables, appearing more regularly, the more complex the codebase is.
Cognitive Complexity
Cognitive complexity, a relatively new measure, assesses how difficult it is for humans to understand the code, considering factors like control flow, data flow, and the inherent readability of the code structure. It looks at things like how the code is organized and if there are complicated parts like nested loops or if statements. The goal is to make the code easier to understand and work with by keeping things simple and organized. By reducing cognitive complexity, it becomes easier for developers to read and change the code, which leads to better-quality software.
Other Measures
There are other measures that sit alongside the methods noted above that can also add to the understanding and measurement of Code Complexity. These fall under terminologies such as;
- Rework Ratio
- no. lines of source code
- Level of interdependence between different modules or components
By also evaluating these additional measures a business is able to glean a complete picture of their Code Complexity.
Why Should you Care?
Hopefully from reading the above explanations it’s clear that yes, some code is more complex than other code. But why does it matter to you? What impact does it have on you, the CEO, CTO, Investor or Product Owner? You wouldn’t be alone if you thought; “OK if I find out that i’ve got a high complexity score, does it really matter?, what am I going to change?” – You’re probably just thinking that some code has to be more complicated because it has greater functionality. So naturally it’s going to have a high score.
And in many instances you would be right, some code needs to be more complicated. But as we’ve stated already we’re looking for code that’s unnecessarily complex.
There are dangers with having highly complex code. You run the risk of increased code defects, increased time fixing bugs, and unreliable testing – which ultimately is going to have. a detrimental effect on your development costs.
The aim for any business developing software is to spend more time building new functionality that’s going to make money than spending time fixing bugs and issues that’s going to cost money. We believe that by decreasing unnecessary complexity, and you will decrease the time to production and increase your future development speed.
By understanding code complexity you will be able to apply it to several practical measures in your software development planning, including:
- Maintainability: Lower complexity generally means the code is easier to maintain and modify.
- Quality Assurance: Complexity measures can indicate potential problem areas that require more rigorous testing.
- Project Estimation: Estimating the time and resources needed for project completion can be more accurate with complexity assessments.
- Performance Optimization: Identifying complex code sections allows developers to target optimizations more effectively.
The Code Registry’s Complexity Score
Among the various methods for measuring code complexity, Cyclomatic complexity stands out to us for its effectiveness and practicality. By providing a clear, quantitative measure of the code paths, it offers a direct correlation with the effort required for comprehensive testing and maintenance. This measure’s simplicity and focus on test coverage make it an invaluable tool for developers and analysts alike.
At The Code Registry, we use a combination of Cyclomatic complexity alongside our proprietary application of AI functions to provide our users a comprehensive code complexity score. Our method is grounded in the proven reliability in identifying potential risks and ensuring that we assess any codebases on our platform to provide insights into their security, but also their maintainability and efficiency. By leveraging Cyclomatic complexity, we equip our users with the insights needed to manage their software assets proactively, emphasizing quality, security, and performance.
By understanding your Code Complexity score in conjunction with our other facets of intelligence and insights you will be empowered to not only better understand the code you have, but also to proactively plan future developments with your team.
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