Automated code review: improve your code review process by automatizing it

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Debugging, staying compliant with coding standards, and strengthening software security. Those are just some of the scopes code review can embrace with specific lightweight techniques. But regardless of the focus: is a simple code review strong enough to make sure there are no human mistakes that put the software development at risk? 

We know that developers have powerful knowledge to be ahead of the issues that may arise. Still, the truth is that nowadays, on the other side of the bridge, there are people creating specific threats that aren’t visible to humans. That’s one of the reasons why having an automated code review is a must for software development.

It’s not about leaving behind both the author’s and reviewer’s expertise. It’s mainly about taking the code review to the next level by broadening the process to get to a safer, high-quality application. Plus, it’s a way to reach the testing phase with a better product with less room for human error.

Let’s delve into what’s precisely an automated code review, why it’s key to delivering high-quality software, some myths about it, and a few tools that might help you adopt it. 

What's precisely an automated code review?

The foundation of automated code review is basically the comparison between the source code against known, standard guidelines. This helps developers identify mistakes and potential security breaches. Automated tools fuel this kind of code review. When an automated tool is integrated into the code review process, it paves the way for tracking teams’ comments and can even offer usage statistics and metrics to support app optimization.

How does the workflow look when using an automated tool? The automated tool will output a report that turns into a pull request that shows all the changes that the developer should apply. If you want to take this further, some automated tools provide the chance to do the changes themselves by merging a pull request upstream.

But, we know, nothing is perfect. Even automated tools can fall into false positives and false negatives. A false positive can result in a waste of time for developers because they’ll have to take time to separate the true positives from the false ones, and they need to pay special attention to that, because missing a true positive could lead to an error not being fixed. While false negatives are mainly about the tool not detecting an error, and letting that error pass the review process if nobody notices it.

Besides the false positives and false negatives issue, an automated code review is still the best way to get safer, high-quality software, and improve its performance.

Why should you embrace an automated code review process?

There are many reasons why. Let’s get into some of the benefits that an automated code review process has to offer. 

1 – The first one is the most obvious: it erases human error. It’s not about eliminating peer reviews or external reviews but about taking advantage of an automated tool to leave behind, especially, the mistakes that are not visible to humans.

2 – Since all the benefits are connected, another one is that an automated code review process can speed up development. Picture this: all those hours that developers won’t spend on reviewing deeply, will be spent on creating more value for the organization. Therefore, it’s also about freeing them to invest their time on stuff they can add more value to.

3 – Plus, automated code review can bring more code quality. Tools can smooth the process of maintaining consistency throughout the development stage. They’re a huge help for standardizing practices, making sure bugs don’t make it to the last part of the development process, and taking unnecessary duplicated code out.

Summing things up: an automated tool is keen on supporting faster, more efficient, and safer applications.

Some automated code review mythbusters

Some people still have doubts about implementing automated code review. They have reasons that, more than reasons, are myths about this automated process. 

One of them goes around development time: it’s said that automated code review slows down the development process. It’s proven that, even though false positives and negatives exist, an automated tool can read thousands of lines of code in seconds. That can’t be compared to doing it manually.

“It’s not accurate”. That’s another argument. Well, hidden paths in code can’t be only interpreted by manual reviews, the truth is that automated code reviewers can also understand them. 

And no, it’s not that expensive either. A huge team of professional coders that work as code reviewers is more expensive than an automated tool. Plus, keep in mind that this automated process aims at identifying errors that can’t be or that are hard to identify manually. Think about the time (and therefore the money) you can save by leaving less room for mistakes in the other stages.

Ready to bring an automated tool to your review process?

Many automated tools are out there, including some empowered with strengthened scanning to reduce false positives and negatives. We’ve selected three tools to give you an overview of what the offerings are. These are Linear B, Codacy, and Code Climate.

  • Linear B shines bright in providing automated metrics about code review time. Plus, it gives you the chance to custom goals to standardize your peer review and make sure all the team is on the same page. If a high-risk issue arises, it will let you know right away by Slack or Microsoft Teams.
  • Codacy works with a lot of programming languages and identifies duplicated code quickly and easily. You can also get your push results as comments in your pull requests as soon as they’re created or as Slack notifications. Its installation and user interface are pretty intuitive and it offers a 14-day free trial.
  • On the other hand, Code Climate is mainly focused on aligning initiatives and strategic priorities to accelerate software delivery. One cool example of what this tool does is its maintainability score from A to F. It assesses duplication, cyclomatic complexity, cognitive complexity, and structural issues. Every technical debt issue goes through its inspection and it estimates how much time it’ll take to solve the problem. The A to F range takes the total remediation time into account.

This was just a quick overview of what an automated code review can do for you. Make sure you’re giving code review the place it deserves in your quality assurance strategy and that you’re not considering it just one more stage of the development process. 

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