Producing quality code has always been a challenge for developers, which has led to clean code standards, development methodologies, and other attempts to make the process easier.
But today’s tightening deadlines and increasingly complex source code is making quality code even harder to write. In fact, studies show that nearly one-third of developer productivity is lost dealing with technical debt. When software teams continue to operate as they always have, developers continue to introduce new issues and perpetuate existing deficiencies.
The problem is that software teams are often forced to balance quality and productivity to ship software faster than ever. Sacrifices in code quality, however, have far greater consequences in the long run.
Let’s take a closer look at why code quality is crucial, and some key steps for improving the quality of code developers produce.
Ensuring developers write quality code can be challenging, but that doesn’t mean companies should ignore the issue. The reality is that deteriorating code quality can impact development velocity, software quality, and business continuity.
As the amount of source code grows, and developers continue to commit the same errors, more time needs to be allocated away from building new features toward fixing bugs. Writing higher-quality code in the first place ultimately is less expensive and less time-consuming in the long run.
Along with the inherent costs of poor code, over time the sacrifices in software quality can make functionality harder to develop. Code quality, therefore, has an enormous impact on developer productivity, user satisfaction, and business success. That’s why we’re taking a deep dive into strategies businesses can use to improve the quality of code they produce.
Software quality should be top of mind for most organizations. Here are our three best tips for improving code quality before issues become unmanageable.
The first step in improving the quality of code is finding out where things went wrong. Most software teams utilize automated test suites and static analysis tools to detect issues before software is released. Many team leads also find it beneficial to have all the code that developers write peer reviewed before it’s merged into the core codebase. These methods for analyzing code can help stop bugs, but they’re not always a reliable assessment of code quality.
The issue with most ways for measuring code quality is that they generate too many false positives. If developers and managers detect inaccurate assumptions about code quality, it will undermine any improvement efforts. Companies, therefore, need a process for analyzing code that generates actionable insights about significant problems within the source code that are too difficult to ignore.
Once issues are discovered, it’s crucial that they’re dealt with immediately. Putting off errors can lead to technical debt and a drop in development velocity over the long term. Software teams need to be regularly refactoring complex code and resolving issues as they arise. That said, software teams should also take time to refactor legacy code to prevent further code decay.
Problems occur when developers recognize existing issues but fail to correct them when they commit new code. This perpetuates a cycle in which code continues to deteriorate, and it becomes unclear from where the defects originated. That’s why it’s critical to change developer behavior to encourage each code commitment to include not just new functionality, but an improvement to the quality of code. Software teams need to stop perpetuating the cycle of code decay.
Without any intervention in developer behavior, they’ll likely continue to make the same mistakes. Targeting low performers with regular coaching can decrease the flow of defects and dramatically improve code quality over time. And while coaching may not be a priority for developers, they can see massive productivity increases that ease their pressure to meet deadlines as well.
The problem is that the lack of accurate data means there’s a constant struggle for developers to get on board with coaching. If there are a lot of false positives when detecting issues or errors are mistakenly attributed to certain developers, there will be a lack of trust in code quality metrics. Companies need transparent insights into repetitive coding behavior that can effectively drive the coaching process.
While identifying and fixing issues is crucial, the best way to improve code quality at large scale is to stop defects at their source through developer coaching. DevCoach is a platform that enables a data-driven approach to coaching developers that leverages sophisticated behavior modeling to track individual performance.
After collecting data from static analysis tools and other sources, DevCoach determines whether code commits perpetuated existing issues or introduced new errors into the codebase. This information feeds developer behavior models that enable personalized insights for coaching developers and tracking whether improvements actually happen over time.
Code quality is critical for organizations today. Download our whitepaper to learn more about why data-driven developer coaching is the key to balancing coding velocity and software quality.