Technical debt builds up when outdated, unused, or poorly written code slows development and increases maintenance. Causes range from rushed planning and shifting requirements to obsolete tech and inconsistent coding practices. Reducing it requires tracking KPIs, regular refactoring, code reviews, automated testing, and better team collaboration. While many tools help manage tech debt, Azul Intelligence Cloud stands out for Java teams by identifying only the code that’s actually running in production. Its Code Inventory and Vulnerability Detection features streamline triage, reduce testing burdens, and avoid false positives—offering real-time, low-overhead insights without steep setup or user minimums.
What Is Technical Debt, and Where Does it Come From?
Technical debt is the result of accumulating code that’s unused or unoptimized for your application, which may also use technology that has been declared End of Life (EOL) by the vendor/community. As you continue to create and add technical debt to your application, software development becomes cumbersome and unproductive. You end up needing to build your own security patches, increase maintenance & QA costs, restructure your code more often, and so on, all of which act as a drag on your development process and limit the time and resources you can devote to creating new features and capabilities that make your product more competitive in the marketplace. Technical debt can accumulate for a few reasons. First, you might rush architectural planning, often due to tight deadlines. Second, the application development lifecycle often involves shifting scope, as product requirements change. previously designed code can become obsolete or less efficient with the new changes. Third, if your code makes use of outdated technologies that are obsolete or deprecated, it becomes harder to maintain your code.
Fourth, junior developers often write inefficient or poorly maintainable code. Fifth, your team might neglect code quality standards and best practices, which include proper commenting and documenting code. This can lead to code that’s difficult to read, understand, work with, and maintain. Sixth, if your testing processes aren’t thorough (along with a thorough process to fix the bugs), then you’ll likely find a lot of undetected bugs and vulnerabilities in your code. These issues compound over time, and you might find yourself stuck spending most of your development resources fixing bugs and vulnerabilities.
How to Reduce Technical Debt
First, you should measure your technical debt in order to understand how much of a problem it is. You can start by establishing key performance indicators (KPIs), such as:
- fixing a certain number of bugs per sprint cycle.
- closing bugs at a faster pace than you’re opening new bugs.
- track how much of your development time is being spent on:
- fixing bugs
- changing/updating existing codes and features
- building new features/capabilities
These measurements will help you maintain a strong focus. To reduce technical debt, you can refactor your legacy code, document and prioritize your technical debt to increase awareness, lead code reviews and dedicated debt repayment work time at specific times of the day or week, adopt automated testing methods, upgrade your older technologies, create modular solutions, collaborate more on code ownership across your team, pair up programmers to work together on code projects, avoid excessive complexity in your code design, train your team to minimize gaps in coding skills, and regularly assess your technical debt.
Comparing Products that Reduce Technical Debt
Because technical debt is a common problem, you’ll find many tools that will help you identify and reduce dead code and technical debt.
| Tool | Description | Key Features | Limitations |
| Azul Intelligence Cloud |
Identifies unused and dead code | Scans code running in production without adding overhead. | Java only. Only scans code being processed by JVMs . |
| CAST Highlight | Assesses codebase health. | Open-source libraries analyze risk. | Data overload from alerts/notifications. |
| Checkstyle | Formats and analyzes static Java code. | Standardize your code formatting. | Java only. Only basic code quality checks. |
| ClickUp | Helps Plan sprints. | Register tech debt, monitor tech debt trends. | Steep learning curve. |
| CodeClimate | Automates code review. | 10-point technical debt assessment. | Complicated configuration. |
| CodeScene | Analyzes code quality. | Code health insights per coder and team. | Doesn’t address all tech debt issues. |
| JIRA | Manages projects. | Customize tech debt workflows. | Complex to set up. Performance issues. |
| Mend.io | Streamlines your app security. | Increase development speed. | Minimum of 25 developers. |
| Perforce | Manages your DevOps. | Test with isolated code branches. | Slow code scans. |
| ReSharper | Analyzes code in Visual Studio. | Restructure and refactor options. | .NET only. Can slow down your system. |
| Selenium | Tests your code quality. | Automated and regression testing. | Web only, not for desktop apps. |
| SonarQube | Inspects code quality and security. | Static analysis and precise feedback. | Generates false positives. |
| Stepsize AI | Tracks tech debt with generative AI. | Project-level insights on data and issues. | Limited programming languages/features. |
| Teamscale | Manages software quality. | Analyze data from different sources. | No AI features. |
About Azul Intelligent Cloud
Azul Intelligence Cloud (IC) features:
- Code Inventory which catalogs running code in=production to identify unused/dead code,
- Vulnerability Detection which continuously detects vulnerabilities using a rapidly updated CVE knowledge base so DevOps team can efficiently triage to help prioritize remediation,
- Historical Analysis which retains your code history to determine if vulnerable code has previously been exploited,
- Real-Time Monitoring to provide accurate data on code usage,
IC includes several key advantages over other tools that help reduce technical debt:
- Comprehensive code-quality checks: IC’s Code Inventory provides thorough code quality reviews by accurately identifying unused and dead code. IC details what custom and third-party code that you actually run in production. By focusing on code that’s being actively used, IC helps you reduce your burden of testing, fixing, and maintaining code unused code.
- User-friendly: You won’t find a steep learning curve with Azul Intelligence Cloud. IC is optimized to be user-friendly and efficient. It’s an agentless cloud service, which means that it won’t require complex installations. Users only need to set up their environment once, and Azul provides detailed documentation to help you get started easily and to help you make the most of IC’s features. IC also provides clear and actionable insight from your production Java runtime data.
- No minimum amount of users: Unlike other services, you can use IC if you’re one person or if you’re setting it up for 100,000 developers.
- Fast code scans: IC’s code scans are designed to be both efficient and thorough. IC uses real-time and historical analysis to monitor the code that’s executed by the Java runtime in production. This process results in detecting vulnerabilities quickly and accurately, without causing you performance penalties. For more information, see IC’s Vulnerability Detection.
- Both web and desktop: IC is compatible with both web and desktop applications. It monitors your Java applications that run in any production environment. IC helps make sure you maintain the same high level of code quality and security standard across different types of applications.
For more information about IC’s key feature sets, see Code Inventory and Vulnerability Detection.
