What Is Cognitive Complexity? Definition & 8 Facts

James Bieri proposed cognitive complexity as a component of personal construct psychology in 1955.Later, the concept was broadened to include human-computer interaction and organizational theory, for which it was initially used to mental health and psychology patients.It refers to a person’s capacity to detect and respond to factors based on past experience and previously built personal constructions.

What Is Cognitive Complexity?

Cognitive complexity is the capacity of individuals to perceive the environment around them. Additionally, it represents the quantity of cognitive processes necessary to execute a task.

There are more steps involved in doing intricate activities than simple ones. Making a sandwich is easier than writing a term paper, for example.

What Is Cognitive Complexity?

Writing the paper requires many additional cognitive processes, such as utilising web resources, conducting competent research, and adhering to a particular style and tone.

Individuals can also assess events more precisely when cognitive complexity enables them to perceive shades of nuance and meaning more vividly.

Life experience and education are the most significant determinants of the cognitive complexity of an individual. Individuals are able to build mental constructions when they are exposed to complicated situations, whether via life experience, education, or training.

The personal construct theory, which asserts that individuals understand the world through mental constructions, elaborates on this view of what cognitive complexity is.

These heuristics expedite the analysis of circumstances and activities by providing individuals with shortcuts.

As an alternative to combing through several notebooks of the same hue, someone might color-code their notebooks to make it easier to determine which notebooks are for specific subjects.

By reducing portions of the problem-solving process to automatic processes, mental constructs facilitate the resolution of complicated issues.

Cognitive complexity is also utilized in computer programming to assist programmers in describing code units. In this context, cognitive complexity refers to how difficult it is to comprehend a program’s code unit.

What Is Cognitive Complexity?

Some functions and classes are clear and straightforward to comprehend, but others have several components, multiple logic breakdowns, and references to other files, making them tough to grasp.

Complex code is typically more prone to errors since there are more potential points of failure during program execution. It also makes it more difficult to build new code that interacts with existing, complicated code, necessitating rewrite to simplify the code.

Uses of Cognitive Complexity Theory

Cognitive complexity is used in software development to define the difficulty of a specific piece of code, as discussed above. However, it is also utilized to create computers that more closely resemble human thought.

Information is processed by computers using binary code, or ones and zeros. They observe the program to run and execute it. They do not pause for thought or provide original answers.

Therefore, software engineers and scientists are attempting to build methods for a machine to think more like a person in order to handle more complicated issues.

Artificial intelligence refers to these systems. The goal of artificial intelligence is to create computers that are capable of complicated cognitive tasks as opposed to simple cognitive capabilities such as perception and memory.

Instead of taking the most direct route to solve an issue, teaching computers to recognize the intricacies of a variety of difficulties enables them to manage more complicated circumstances in an optimal manner.

What Is Cognitive Complexity?

Cognitive complexity in organizations refers to the capacity to recognize patterns inside an organization in order to improve procedures for efficiency.

This talent entails perceiving the organization in both a wide and narrow perspective. When there are fewer factors to consider, optimizing a portion of an organization is a lot simpler task.

To optimize a complete business, one must be able to identify possible bottlenecks, comprehend supply and demand, and grasp market trends, among other things.

If a firm is underperforming, its management must be able to identify the underlying causes and devise remedies. Cognitive complexity enables individuals to think creatively and discover novel solutions.

Cognitive Complexity Communication

Cognitive complexity in communication refers to the number of psychological constructs an individual might use to describe someone. These psychological constructs generally refer to personality traits, like “energetic” or “caring.”

Those who are more perceptive of others tend to use more psychological constructs to describe people. These people have higher interpersonal cognitive complexity, allowing them to notice more details about a person than somebody with less skill.

An average individual might describe someone as “friendly,” while the person with higher interpersonal cognitive complexity will notice that they are also giving and self-confident.

What Is Programming Cognitive Complexity?

After reading about cognitive complexity in general, it is simple to apply the notion to software engineering.

Cognitive complexity in software development quantifies how difficult it is to comprehend a specific piece of code, such as a function, a class, etc.

This has significant effects on the quality of a software project.

Why Is Cognitive Complexity Dangerous?

High cognitive complexity is one of those software metrics that is both a symptom and a source of additional difficulties. As a result, resolving it is incredibly profitable, as it entails treating present problems and preventing future ones.

Next, we will discuss the sources of cognitive complexity in coding. Let’s now concentrate on some of the difficulties it can cause.

Three frequent challenges caused by cognitive complexity in coding are:

What Is Cognitive Complexity?

Complex code is more prone to errors. If engineers find a piece of code difficult to comprehend, it is more probable that they will create bugs.

Complex code makes onboarding new team members more difficult. When joining a team, it takes time to become familiar with the codebase. That is very typical. However, too complicated code may make this learning curve unreasonably steep.

Complex code increases rework. If a piece of code is too complicated, developers may design new code that interacts with it incorrectly. Then, upon discovering the problem, they will have to redo the code they just created.

What Causes Cognitive Complexity?

Now, let’s examine some of the most important reasons of cognitive complexity. Keep in mind that the nature of the following factors varies.

Some of the issues are inherent to the project itself. There is also a single reason why something is fundamental to the domain and unavoidable: high essential complexity.

A last source of cognitive complexity is a lack of education: these challenges are the result of an engineer’s lack of knowledge and experience.

Cyclomatic Complexity

The cyclomatic complexity of a code block (e.g., a function) quantifies the number of execution paths.

This statistic is very essential when it comes to testing, as it helps to specify the minimal number of test cases required for complete branch coverage.

What Is Cognitive Complexity?

However, cyclomatic complexity also influences cognitive complexity. In general, it is more difficult to comprehend and traverse code with a high cyclomatic complexity.

Poor Naming

If you have been a software engineer for any length of time, you are aware of how difficult naming is. Unfortunately, this means that many, if not the majority, of the names in our codebases are not optimal.

Poorly named code artifacts necessitate additional effort on the part of code readers in order to determine their purpose. Consequently, cognitive complexity increases.

Poor Architectural Decisions

The architectural level may also influence cognitive complexity. Excessive coupling between modules is one example of poor architecture that might have a negative impact on the system’s overall comprehensibility.

One more instance? Poor division of responsibilities. For instance, business domain code associated with presentation layer issues.

Such mismatches are a source of cognitive complexity: engineers are perplexed — and rightfully so — when modifying code in a particular layer results in effects in apparently unrelated portions of the application.

Large Functions or Classes

Large chunks of code, such as classes, functions, and modules, are not always more difficult. However, due to their length, they indicate a greater possibility of complexity: more code = more opportunities for complicated code.

High Essential Complexity

Simply stated, unintentional complexity is “poor” complexity.

We introduce unintended complexity to our projects owing to our limitations as software engineers and, more generally, as humans. This is the sort of project complexity that should be reduced.

Essential complexity, on the other hand, is inherent to the area we’re working in. There is no way to diminish it further; thus, we must deal with it.

Some areas are just more complicated than others, and this complexity influences the project’s total cognitive complexity.

Not Following Established Conventions

Some programming languages and frameworks are notoriously prescriptive, even down to the project folder structure and the naming conventions for files, functions, and classes.

There are also technology stacks that are less biased. Even so, they set common coding standards that everyone producing code in that language should adhere to.

There are engineers who view such traditions to be oppressive and who strive to oppose them. This increases cognitive complexity since those used to the norms will have a more difficult time navigating the project.

Cognitive Complexity in Software: Can You Fix It?

A concise yet comprehensive explanation of cognitive complexity in software has just been presented. You are now aware of what it is, its origins and effects, and why it may be quite a headache.

The next logical issue for the majority of people is how and whether cognitive complexity can be fixed.

You may have heard the adage, “You can’t improve what you don’t measure.” Therefore, evaluating cognitive complexity is the first step in addressing it.

What Is Cognitive Complexity?

Certainly, there are subjective elements to cognitive complexity. However, there are objective means by which cognitive complexity may be measured. And this is accomplished by monitoring relevant metrics.

3 Metrics For Measuring Cognitive Complexity

Measurable variables such as cyclomatic complexity and code length serve as predictors of cognitive difficulty.

Also, excessively rewritten code, or code that endures a great deal of churn or “rework,” is typically a bad indicator.

One of the most prevalent causes for such revision is that the developers are having difficulty with the code. This indicates that the code may be overly complicated.

Here are three indicators that you should start monitoring daily to boost cognitive complexity in your codebase:

Refactoring describes modifications to legacy code that have been updated. Any code introduced to the codebase by LinearB more than 21 days ago is considered legacy code.

Some degree of code refactoring is acceptable and even essential for quality improvement. It is not advised to do a large number of refactorings in a single release, as doing so has a greater likelihood of hurting current functionality.

Pull Request Size – Pull request size is a statistic that measures the average number of lines of code that a pull request modifies.

Review Depth – Review depth is a measurement of the average number of comments per pull request review. This measure indicates the quality of the review and the thoroughness of the review process.


Cognitive complexity describes a person’s capacity to perceive objects in the surrounding environment. Additionally, it indicates the amount of cognitive processes necessary to solve an issue or finish a job.

Those with a higher level of cognitive complexity may see shades of delicacy and significance. They have the life experience or education that has allowed them to acquire this level of cognitive complexity, because these events and education aid in the formation of mental constructions.

Mental constructs are mental processes’ short-cuts, allowing humans to assess events rapidly. Also, psychological constructs characterize the personality qualities utilized in cognitive-communication complexity.

Individuals with a high level of communicative cognitive complexity are able to perceive more nuanced emotions and personalities in others.

Computer science and organizations both utilize the phrase cognitive complexity. Cognitive complexity often relates to the difficulty of comprehending a unit of code in software.

However, it is also used to define the level of cognition in artificial intelligence, as computer scientists and software engineers strive to educate computers to perceive more nuances so that they may be more effective problem solvers.

Cognitive complexity is utilized in businesses to encourage individuals to think outside the box and identify more innovative solutions to commercial challenges.


A method’s cognitive complexity is based on a few simple rules: Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one. Code is considered more complex for each “break in the linear flow of the code”
It further suggests that cognitively complex persons are characterized by chronic trait-based differences in motivation and ability to think complexly. Keywords. individual differences, cognitive complexity, integrative complexity, social cognition.
Basic criteria and methodology A Cognitive Complexity score is assessed according to three basic rules: Ignore structures that allow multiple statements to be readably shorthanded into one. Increment (add one) for each break in the linear flow of the code. Increment when flow-breaking structures are nested.
so here are some tips to reduce it,
  1. Try to use Anonymous Object instead of the creation of variables.
  2. Reduce multiple if-else statements in your code.
  3. Refactor your code.
  4. Reduce No. of parameters of the method
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Pat Moriarty
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