Code Reviewing: Finding Bugs and the Art of Crushing ‘Em

Code review is an essential part of the software development process. It is a crucial step that ensures the quality and reliability of the codebase. It requires a keen eye for detail, excellent communication skills, and a deep understanding of software design principles.

In this article, we’ll delve into the art and science of code reviewing, exploring how to do it well, how to avoid common pitfalls, and why it matters.

Code review is not a battlefield

Code review is not a competition, nor is it a battleground. The reviewer is not an opponent of the author; both of them are aligned on the same goals - solving product problems and making a high-quality codebase. Therefore, it’s essential to approach code reviewing with a positive and constructive mindset.

Code reviewing is a collaborative process that involves multiple stakeholders. The primary purpose of code review is to ensure that the code is of high quality, meets the requirements, and adheres to the coding standards. The reviewer’s job is to identify issues, suggest improvements, and ensure that the code follows the best practices.

The author’s job is to receive feedback, implement the changes, and ensure that the code meets the requirements and standards.

To make code review a positive experience, both the reviewer and the author should treat each other with respect, empathy, and professionalism. It’s essential to avoid personal attacks, criticism, or blame games. Instead, focus on the code and how to improve it. Remember, the code is not the author, and the author is not the code. Therefore, it’s essential to separate the code from the author’s personality, opinions, or ego.

Automate the routine: Let your computer do the heavy lifting

In every code review, there are certain questions that keep popping up. Questions like

”Why did you use this naming convention?“,

”Can you reformat this block of code?”, or

”Why did you use this style instead of that style?”

These questions can get repetitive, and answering them over and over again can be time-consuming.

That’s where automation comes in. By automating routine tasks like formatting and naming conventions, you can save time and improve consistency in your code reviews. For example, you can use linters and style checkers to automatically detect and fix issues with code style and formatting. This not only saves time but also ensures that your codebase follows consistent and best practices.

Another way to automate routine tasks is to use code review tools that integrate with your version control system. These tools can automatically detect changes in your codebase and notify you of any issues that need to be addressed. This streamlines the code review process and makes it more efficient.

Imagine you’re working on a team that follows a strict naming convention for variables and functions. You have to constantly check and fix naming issues during code reviews. By using an automated tool like ESLint, you can automatically detect and fix naming convention issues. This saves you time and ensures that the codebase follows the team’s naming convention consistently.

Code style: From ugly duckling to beautiful swan

“To style, or not to style? That is the question.”

Okay, so maybe that’s not the exact quote from Hamlet, but as developers, we do face a similar dilemma when it comes to code styling. Sure, we could just write our code however we want and hope for the best, but that can lead to errors, inconsistencies, and a lot of wasted time. That’s why we need to take code styling seriously. And while tools like Prettier and ESLint are great for automating basic code formatting, there are some advanced techniques for improved coding style.

By using techniques like configuring our editor settings, using CSS preprocessors, and adopting a style guide, we can take our code styling to the next level and make our code more readable, consistent, and maintainable.

Tests: The power of superhero-grade code quality assurance

Testing ensures that your code works as intended and catches any bugs before they cause trouble in the production environment. But testing can be a time-consuming process, especially when you’re working on complex projects.

That’s where automated testing comes in. By using a continuous integration (CI) system, you can automate the execution of tests and get instant feedback on their status. This means that you don’t have to manually test each feature, saving you time and effort.

But there’s more to automated testing than just running tests automatically. Have you heard of mutation testing? It’s a fancy name for intentionally introducing small changes (called “mutations”) into your code to see if your tests catch them. It’s a powerful way to ensure that your tests are thorough and catch any potential issues in your code.

Another advanced technique is property-based testing. Instead of manually writing test cases, you define properties that your code should follow, and a tool generates test data that satisfies these properties. It’s like having a robot assistant that helps you test your code!

For instance, imagine you’re working on a machine learning project that processes large amounts of data. By using mutation testing, you can ensure that your tests catch any issues in the code that handles this data. Similarly, property-based testing can help you test complex algorithms by generating test data that covers all edge cases.

(DRY) Don’t Repeat Yourself: Eliminating Code Duplication

Code duplication is a common problem in software development. It occurs when the same code is repeated in multiple places, leading to maintenance issues and bugs. Code duplication can also lead to inconsistencies and errors in the codebase. Therefore, it’s essential to identify and eliminate code duplication during the code review process.

There are several tools that can detect code duplication, such as CodeClimate and SonarQube. These tools can analyze the codebase and provide a report on code duplication across all applications. They can also suggest fixes to eliminate code duplication.

By addressing code duplication during the code review process, the codebase becomes more maintainable, reliable, and consistent.

Gaining insights into your code’s performance and potential issues

Code analysis is a process that involves the automated analysis of code to identify issues, such as bugs, performance problems, security vulnerabilities, and other code smells. Code analysis tools can provide insights into the codebase’s overall health and quality.

There are several code analysis tools available, such as CodeClimate, SonarQube, and ESLint. These tools can be integrated with the code repository and run on each code review. They can provide a report on code quality, highlighting potential issues and suggesting fixes.

Code analysis is a crucial step in the code review process. It can help identify issues that are difficult to detect manually and improve the overall quality of the codebase.

Ahoy, we need to focus on business goals too, the ‘why’ behind the code

Before we dive into the code, let’s take a step back and look at the big picture. Why was this code written? What problem does it solve? What are the business requirements? It’s essential to understand the why behind the code before we can evaluate the how.

Once we understand the business goals, we can evaluate the code from a business perspective. Does the code meet the business requirements? Does it solve the problem it’s intended to solve? Are there any edge cases that the code doesn’t handle? By answering these questions, we can ensure that the code is aligned with the business goals.

Implementation: The nitty-gritty of the code

Now that we understand the business goals, let’s dive into the code. Implementation covers various areas, such as security, error handling, performance, integration, and logging. Let’s take a closer look at each of these areas.

Security: Protecting the fort

Security is a crucial aspect of software development. We need to ensure that the code doesn’t introduce any security vulnerabilities. So, let’s put on our security hats and ask ourselves the following questions:

• Does the code introduce any security vulnerabilities, such as SQL injection, cross-site scripting, or DDoS attacks?
• How would the code behave under attack? Is it passive or active in defending against attacks?
• Does the code adhere to security best practices and guidelines?

Remember, we need to protect the fort and ensure that the code is secure.

Error handling: Prepare for the worst

Errors and failures are a fact of life in software development. Therefore, it’s essential to handle errors correctly and gracefully. Let’s ask ourselves the following questions:

• Does the code handle errors correctly and gracefully?
• How does the code behave in case of errors or failures?
• Is the error handling robust and reliable?

By preparing for the worst, we can ensure that the code behaves as expected and doesn’t crash unexpectedly.

Performance: Speed racer or slowpoke?

Performance is another critical aspect of software development. We need to ensure that the code doesn’t negatively impact the application’s performance. So, let’s ask ourselves the following questions:

• Does the code impact the application’s performance? If yes, how significant is the impact?
• Are there any memory leaks caused by the code?
• Is the code optimized for performance, and are there any areas where it can be further optimized?

Remember, we want the code to be a speed racer, not a slowpoke.

Integration: Playing well with others

Integration is another critical aspect of software development. We need to ensure our code integrates well with the existing codebase and systems that it interacts with.

So, let’s ask ourselves the following questions:

• How would our code work with the existing codebase?
• Does the code increase coherence in the codebase?
• Is the code modularized and easily swapable with better implementations in the future?
• Is the code compatible with older versions of the application?

By playing well with others, we can ensure that the codebase is maintainable, reliable, and consistent.

Logging and tracing: Sherlock Holmes to the rescue

Logging and tracing are crucial for debugging and troubleshooting. We need to ensure that the code has adequate logging and tracing mechanisms. So, let’s ask ourselves the following questions:

• Are there enough logs and traces in the code?
• Are the logs and traces relevant and informative?
• Does the code adhere to the logging and tracing guidelines and best practices?

By becoming the Sherlock Holmes of logging and tracing, we can identify issues and troubleshoot them effectively.

Code Review: Wrap it Up!

Code review is a critical step in the software development process. It ensures that the code is of high quality, meets the requirements, and adheres to the coding standards. To make code review a positive experience, it’s essential to approach it with a positive and constructive mindset. Code reviewing is a collaborative process that involves multiple stakeholders.

Automating routine tasks, such as code style, tests, code duplication, and code analysis, can improve the efficiency and reliability of the code review process. By automating these tasks, the reviewer can focus on more critical issues, such as design, architecture, and functionality.

Code review is not a one-time event; it’s an ongoing process that should be integrated into the software development lifecycle. By making code review a regular part of the development process, the codebase becomes more reliable, maintainable, and consistent.