Slower Development Velocity
Development becomes increasingly slow, and new features take longer to implement than expected. Teams spend more time troubleshooting or maintaining existing code than building new functionality.
Example: A feature that should take a week takes three weeks because developers struggle with legacy code and dependencies.
Frequent Bugs and Issues in Production
Code changes introduce unexpected side effects, causing more bugs to appear with every release. These bugs often impact unrelated parts of the system, indicating tightly coupled or fragile code.
Example: A minor UI update accidentally breaks the checkout flow, requiring an emergency fix.
High Effort in Onboarding New Developers
New developers take an unusually long time to understand the codebase, and existing developers spend significant time guiding them. This is often due to poor documentation, convoluted code, or inconsistent coding practices.
Example: A new hire needs months to become productive because of unclear architecture and lack of documentation.
Code is Hard to Maintain or Extend
Developers frequently complain that code is difficult to change without breaking something. Small changes require navigating a complex web of dependencies, making the system fragile and error-prone.
Example: Adding a new field to a form requires updating multiple files and configurations across different modules.
High Number of Workarounds or Temporary Fixes
There are numerous “quick fixes” or patches scattered across the codebase, often with comments like "TODO: Refactor later." These solutions become permanent over time, contributing to an unmaintainable codebase.
Example: Hardcoded values or duplicated logic are scattered throughout the code, causing inconsistencies.
Inconsistent Code Quality Across Modules
Different parts of the system reflect varying levels of code quality, often due to changing teams, rushed development, or lack of refactoring. The inconsistencies make it harder to implement new features consistently across the application.
Example: Some modules follow strict design patterns, while others contain spaghetti code and lack structure.
Outdated Dependencies or Technologies
The system relies on outdated libraries, frameworks, or tools that are no longer supported or actively maintained. Updating them becomes increasingly challenging, compounding the technical debt.
Example: The product depends on a deprecated library, making it difficult to adopt new features or security patches.
Mounting Backlogs of Technical Tasks
Tasks related to refactoring, performance optimization, or fixing bugs accumulate in the backlog and rarely get prioritized. Teams are focused on delivering new features, leaving existing issues unresolved.
Example: A ticket to refactor a core module has been sitting in the backlog for months without attention.
High Test or Deployment Failures
Test suites or deployment pipelines fail frequently, indicating brittle automation or poorly written tests. This increases the time and effort required to release new software reliably.
Example: A small change triggers dozens of test failures, even though the functionality itself works as intended.
Growing Frustration Among Developers
Developers feel burned out or demotivated due to the difficulty of working with the codebase. This is often a consequence of dealing with inefficient processes, fragile systems, and unclear ownership of legacy code.
Example: Developers express frustration in meetings, complaining that "everything breaks when we try to change anything."