In the fast-paced world of software development, maintaining clean, efficient, and easy-to-navigate code is paramount. However, as projects grow in complexity and teams expand, it’s not uncommon for code quality to deteriorate. It is up to product owners and product managers to be informed on the telltale signs that developers may be writing bad code and offer strategies to address these issues.
By identifying these indicators early and implementing corrective measures, development teams can ensure their codebase remains robust, maintainable, and scalable.
If you notice any of these signs in your development project, it might be time to take a close look.
UI inconsistencies usually signal poor standardization, where there is a lack of reusable components or consistent styling frameworks. Not only does this make the codebase disjointed, but extremely hard to maintain. You can easily fix issues across multiple components when they share the same structure.
For instance, you might have a registration page with an input field saying “Email Address” using 14px font. But then, the same component appears on another page, just says “Email,” and has 12px font. This shows that these two elements were developed independently instead of sharing variables and styles.
When a development project lacks code style guidelines, the whole process becomes riddled with ad-hoc practices. This creates a lack of consistency, where you can have one developer using camelCase to name variables while another is using snake_case.
This can lead to a lot of confusion and errors, especially if the codebase is large. Also, it can make collaboration a challenge, which can hinder the project’s maintenance and scalability. Furthermore, the codebase can become hard to understand, especially for new developers.
There are a few signs that can signal developers are using GPT-written code; although, actually figuring this out can be tricky. These include generic naming conventions, repetitive code, lack of contextual understanding or patterns, and unnecessary or irrelevant lines. Some GPT instances add line-by-line comments explaining obvious functionality–which is unnecessary.
If there are way too many instances of these, you can reasonably suspect that GPT was used.
One thing to note is that there is nothing inherently wrong with using GPT-written code. As long as developers don’t rely too heavily on it and take the time to understand, refactor, and optimize it before working it into the project, it can be a valuable tool. These steps can ensure the code adheres to the guidelines, architecture, and requirements, without introducing technical debt and security vulnerabilities.
Developers should not be copying and pasting logic into multiple places instead of encapsulating it in reusable components like functions and classes. This is a clear violation of the Do Not Repeat Yourself (DRY) principle.
When code is duplicated across a project, errors and inconsistencies are more likely. Also it means increased maintenance effort since a mistake means all duplicated instances need to be fixed. This lowers the efficiency of developers and leads to unnecessary and costly delays.
The exception is boilerplate code, but learning that is overkill for a non-technical person.
Big companies can often take a month to merge code. That means code reviews taking too long is not a direct hint that there is bad code being written. But if this is not the case, then you need to look into it.
In my experience, code reviews take longer than expected because developers repeatedly make mistakes that are in conflict with the documentation. Miscommunication when creating or updating documentation is usually the problem. There is usually not enough code discussion or moderation, leading to lack of clarity, inconsistent interpretations, insufficient feedback, and too many assumptions.
Other reasons developers can make easily avoidable mistakes are a lack of familiarity with the guidelines, time pressure, switching between different projects (it’s easy to confuse practices this way), and dealing with complex code.
When developers don’t thoroughly test the code, it can lead to the same bugs reappearing. Testing the code, whether through unit tests, integration tests, or other types of tests, can help catch bugs early before they become deeply ingrained into the codebase. If this is not done in an efficient manner, the code can easily become unreliable.
Test-Driven Development (TDD) can be an excellent preventive measure, as it encourages developers to write tests before implementing features. While TDD promotes good code practices from the start and helps maintain code quality, TDD is not always feasible due to time constraints, project complexity, or team expertise.
Nevertheless, when possible, TDD can significantly reduce recurring bugs, as well as improve overall code structure and architectural decision making.
When developers start writing messy or inefficient code, priority should go toward taking corrective action. Getting developers back on track involves a combination of strategic hiring, external expertise, and continuous improvement practices.
Here are some effective approaches to address and rectify issues in code quality.
Senior developers can help get the team back on track when the team starts writing mess code. They can do this by being a role model, mentoring junior developers, communicating effectively, facilitating discussions, and encouraging confidence in their colleagues. In this case, true seniority isn’t just about years of experience, but leadership ability.
Hiring senior developers with these qualities will improve code quality, speed up learning, and tackle technical challenges. This approach elevates the entire team’s performance and fosters a positive development environment.
Hiring external code reviewers is particularly useful for teams looking to improve their development processes and code quality quickly. They’re also useful for teams where one person is in charge of a single technology (e.g., one Android Engineer in the company).
With external code reviewers, you get fresh perspectives and unbiased insights into your codebase. They can identify issues, which developers can easily miss, and suggest best practices that can help maintain high code quality standards.
Continuous code refactoring involves restructuring existing code without changing any of its external behavior. This process helps eliminate technical debt, enhances readability, and makes the codebase more efficient.
You should allocate some resources toward code refactoring to keep the code clean and up-to-date with best practices.
By hiring a mentor for your organization, you can transform not only the code your developers write but also enhance productivity and cohesion across all levels.
For developers, a mentor can offer personalized guidance through project coaching, guidance, and Scrum. They can foster a culture of continuous learning, taking ownership of decisions, and embracing new technologies, while ensuring that they always work SMART.
Even for non-technical personnel like designers, a mentor can be beneficial in helping them understand the technical constraints of a project, leading to more integrated design solutions. Furthermore, a mentor can offer insights that help managers and C-level executives understand their engineers and make strategic decisions that are aligned with the technological capabilities of their teams.