The impact of low-quality code

Functional systems can mask inefficient source code that is slowing you down and limiting your results

Software has become the backbone of countless industries and the quality of code that powers these applications has never been more critical. While features and functionality might take centre stage, the quality of code that lies beneath them can significantly impact a software project’s success.

Low-quality code may not cause immediate problems, but it can lead to more bugs, longer development times, increased costs, and even unhappy customers. Research from the Association for Computing Machinery reported that up to 42% of a developer’s time can be wasted due to technical debt caused by poor code quality.

In the first of our two-part guide, we’re going to help you measure your code quality before exploring what causes low-quality code and the consequences it can have on your software development projects.

Decoding code quality

Code quality can be defined as a measure of how well your code adheres to best practices and design principles. It’s a reflection of how easily your code can be read, understood, modified, and maintained by others – not just the person who wrote it.

While there is no one-size-fits-all definition for code quality, it generally encapsulates these core concepts: readability, maintainability, efficiency, and robustness.

Readability

Readable code is easy to understand and follow. It has a clear structure, follows naming conventions, and includes comments where necessary. It reduces the time required for other developers to understand and work with the code.

Maintainability

Maintainable code is designed to handle changes easily. Whether it’s fixing bugs, adding new features, or improving performance, maintainable code should allow these tasks to be performed without causing new issues or breaking existing functionality.

Efficiency

Efficient code performs its intended function without wasting resources. It minimises the use of CPU time, memory, and other system resources to deliver optimal performance.

Robustness

Robust code is resilient to unexpected inputs or scenarios. It doesn’t crash or produce incorrect results when faced with edge cases or errors. Instead, it has mechanisms in place to manage these situations appropriately.

What causes low-quality code?

1. Lack of planning and design

Good software starts with good design. Taking the time to plan your architecture, define your classes and functions, and think through your algorithms can go a long way in producing high-quality code. Without a clear blueprint, the code can become unorganised and difficult to maintain.

2. Ignoring coding standards

Coding standards provide guidelines on how to write code, including naming conventions, formatting rules, and best practices. Ignoring these standards can lead to inconsistent and messy code that is hard to read and understand.

3. Inadequate testing

Testing is crucial for ensuring code quality. Without adequate testing, bugs and errors can go unnoticed until they cause problems down the line. Moreover, tests serve as a form of documentation, explaining what a piece of code is supposed to do. Ignoring or rushing tests can significantly lower code quality.

4. Skipping code reviews

Code reviews are a valuable tool for maintaining code quality. They provide a platform for developers to learn from each other, catch bugs early, and ensure that the code adheres to coding standards. If you aren’t holding code reviews, your development team is missing an opportunity to learn and improve their future work.

5. Succumbing to deadline pressure

When faced with tight deadlines, developers may be tempted to cut corners to get the job done faster. This could mean ignoring best practices, skipping tests, or leaving ‘technical debt’ unresolved. While this may help meet the deadline, it often leads to lower code quality and more work in the future.

6. Lack of continuous learning

Software development is a rapidly evolving field. New tools, practices, and paradigms emerge regularly. Organisations that don’t keep up with these changes risk using outdated or inefficient methods, which can negatively impact code quality.

Defining code quality metrics

As we delve deeper into the world of code quality, it’s imperative to understand that improving code quality is not simply a conceptual exercise. It requires concrete, measurable changes that can be tracked over time. To do this effectively, we need to define metrics that can quantitatively assess various aspects of our code.

These metrics serve as both a diagnostic tool and a progress tracker, helping you identify areas that need improvement and monitor how effective your efforts have been.

Lines of code (LOC)

While a simple metric, LOC can provide a rough estimate of the size of a codebase or the complexity of a function or module. However, it should not be used as the sole measure of code quality as it doesn’t take into account the readability, maintainability, or efficiency of the code.

Code coverage

Code coverage measures the amount of code that is covered by unit tests. It provides an indication of how thoroughly your code is being tested, which can help identify areas of the code that may be at risk of containing undiscovered bugs.

Code duplication

Code duplication refers to identical or nearly identical blocks of code appearing in more than one location within the codebase. High levels of code duplication can lead to maintenance difficulties and inconsistencies, as changes made to one section may need to be replicated in all other similar sections.

Technical debt

Technical debt refers to the implied cost of rework caused by choosing the quick and dirty solution instead of the best overall solution. High technical debt suggests that the codebase may contain a significant amount of suboptimal or ‘hacky’ solutions that will need to be refactored in the future.

Coupling between object classes

Coupling refers to the degree to which one class knows about another class. If classes are tightly coupled, a change in one class necessitates changes in the classes it is coupled with, making the code harder to maintain. Lower coupling is generally preferable.

Bug rate

Bug rate refers to the number of bugs found per lines of code over a specific period. A high bug rate could indicate issues with code quality, testing procedures, or both.

Each of these metrics brings a different perspective to code quality, and together they can provide a comprehensive view of the health of your codebase.

The cost of poor code quality

Understanding the cost implications of poor code quality is critical in appreciating the importance of investing in code quality improvement initiatives.

Direct impacts on your business

Increased development time

Poor code quality can significantly extend development time. Code that lacks clarity or is structured poorly requires more time for developers to decipher and modify. Identifying and fixing bugs becomes a time-consuming task, as the code makes it difficult to identify where issues originate. This results in a slower development pace and delays in software release schedules.

Higher maintenance costs

Poorly written code can be expensive to maintain. It tends to be more prone to bugs and errors, which require regular patches and fixes. The resources spent on repeatedly identifying these issues, rectifying them, and testing the solutions could be better utilised in enhancing existing features or creating new ones. Over time, these additional costs accumulate, making the software significantly more expensive to maintain than initially anticipated.

Reduced software performance

Suboptimal code directly impacts software performance. It may lead to inefficient use of system resources, longer response times, and reduced overall system reliability. Poor code quality can also compromise the reliability and security of the system, increasing the likelihood of crashes or data loss.

Indirect impacts

Decreased team morale

Working with low-quality code can be a source of significant frustration for developers. Constantly having to decipher complex, poorly-documented code to make even minor changes can lead to dissatisfaction and burnout. In turn, this can lead to a drop in productivity as motivation levels plummet. In a field where innovation and problem-solving are key, a demotivated team can significantly hinder progress and creativity.

Difficulty in onboarding new team members

When your codebase lacks readability and robustness, bringing new team members up to speed becomes a daunting task. They may struggle to understand the logic behind the code, the architecture, or even the purpose of certain modules or functions. This steep learning curve extends the onboarding process, delaying the time it takes for new hires to become fully productive members of your team.

Damage to brand reputation

Frequent software issues resulting from poor code quality can lead to customer dissatisfaction. Frequent crashes, performance issues, or unanticipated behaviour frustrates users, leading them to explore alternatives. As negative user experiences pile up, these can translate into damaging reviews and feedback that harm your company’s reputation. Over time, this could lead to loss of customer trust, difficulty in acquiring new customers, and even potential loss of business opportunities.