How to Find & Fix Technical Debt: A Developer’s Guide

It was meant to take two days. It took two weeks, broke three tests, and now no one wants to touch that code. This is technical debt.

This guide shows how to classify debt, find risky parts using data, prioritize fixes, and make changes safely – while preventing new debt.

FIX YOUR TECH DEBT

Key Points

• Classify Your Debt: Not all debt is the same. Separate code, architecture, testing, and other types to choose the right fix.

• Make Debt Visible: Use a mix of automated analysis, architectural reviews, and team knowledge to find and measure debt hotspots.

• Prioritize: Focus on the 20% of debt items causing 80% of the pain

• Fix Incrementally and Safely: Fix in small, safe steps.

• Prevent New Debt: Add guardrails with automation, clear standards, and a set budget for ongoing refactoring.

1. How do you quickly assess the technical health of an organization?

The single main thing that lets you know you have technical debt is a noticeable and consistent drop in development velocity. Work that should be simple, like adding a feature or fixing a bug, starts taking much longer. Developers spend time fighting the codebase instead of building. So, the one yes/no question a person should ask themselves to know if they have technical debt is:

Does making a simple change to the code feel disproportionately difficult or slow?

Of course, this is not the only signal, but this friction is the clearest sign of technical debt and directly slows development. Yet, if that’s not enough for you, here are more questions to ask yourself:

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2. How to find and measure your technical debt?

You cannot fix what you cannot see. You can identify technical debt using static analysis tools, architectural reviews, and team workshops. To measure it, go for tracking complexity, test coverage, and team-reported pain points.

Automated Analysis

• Code Scanners: Tools like SonarQube claim they can scan code for bugs, security issues, and code smells, and give clear metrics to track. You should also be able to integrate these into your CI/CD pipeline with a “Quality Gate” to prevent new debt from being introduced.

• Key Metrics: Example metrics to quantify your debt:

  • Cyclomatic Complexity: Measures how complex a function is. It counts decision points. The higher the value, the more complex the logic is, and the code is harder understand, test, and maintain. A value over 9 or 10 is a red flag and you should probably* refactor the code. (* Widely used threshold, but not universal. Many teams tolerate functions with complexity 12–15 if testable and stable. Use as guideline, not absolute rule.)

    • Cyclomatic Complexity = 1 + (Number of Decision Points) Decision points are keywords that split the path of your code, such as:
      • if / else
      • while / for
      • case (in a switch statement)
      • Logical operators like && (AND) and || (OR)

      Example 1: Simple function

      function getFullName(firstName, lastName) {
        return firstName + " " + lastName; // No decisions here
      }
      

      • Decision Points = 0
      • Complexity = 1 + 0 = 1.

      Example 2: A little more complex

      function getGreeting(name) {
        if (name) { // <-- 1st decision
          return "Hello, " + name;
        } else {
          return "Hello, stranger.";
        }
      }
      

      • Decision Points = 1 (if / else statement)
      • Complexity = 1 + 1 = 2.

  • Technical Debt Ratio (TDR): Compares the cost to fix your debt versus the cost to rebuild the system. It is calculated as $TDR=(RemediationCost)/(DevelopmentCost)$. A TDR of 5% or less is considered healthy (according to the SonarQube guidance; it’s not an industry standard).

  • Test Coverage: The percentage of your code executed by automated tests. Low coverage = a high risk of introducing regressions when making changes.

Manual & Collaborative Discovery

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Yet, automated tools don’t have the context. That’s why your team’s experience and the good old “pen & paper method” might be the best way to identify the most painful debt.

Architectural reviews help you see if the system’s design still supports goals like maintainability, security, and scalability. Any gaps you find point to architectural debt.

Hotspot analysis shows where the worst technical debt lives. These are complex parts of the code that change often. Use version control data to spot files with high churn, then check how complex they are.

Finally, team workshops. You map out the system and have the team mark which parts are hardest to work with. The most painful areas become clear, and you get a shared view of where to focus next. Here, Event Storming can help.

3. How to classify technical debt?

Giving it the right name will help you move beyond a generic complaint of “bad code” to a specific problem you can do something about.

What is tech debt? Technical debt refers to the cost of shortcuts in software development that make future changes harder and riskier.

Software expert Martin Fowler classifies debt as either deliberate or inadvertent and prudent or reckless. You might take Prudent and Deliberate debt to meet a deadline with a plan to repay it. Yet, Reckless and Inadvertent debt comes from lack of skill or care. You’ve got to understand whether the root cause is a strategic choice or a need for better training and processes.

Read our related article for a more comprehensive list of technical debt types (that includes both more “technical” and “business” types of the debt). For specifically “tech-tech” types, look at at the table below.

4. How to prioritize which technical debt to fix first?

You can’t fix everything at once, so treat debt repayment as an investment portfolio. Here, the Pareto rule will apply as well: focus on the 20% of debt items causing 80% of the pain.

Assess each debt item across these four dimensions:

And here are some more aspects to think about from user @vassadar in r/salesforce:

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5. How to fix existing tech debt?

The prerequisite you need for fixing existing tech debt is automated testing. These tests give quick feedback and strong “yes” to change structure without breaking behavior.

Micro-Level Fixes: Code Refactoring

For localized code debt, use disciplined refactoring techniques. Coined by Martin Fowler, refactoring alters internal structure without changing external behavior.

• Extract Method: Take a fragment of code from a long method and move it into its own new method with a descriptive name. This makes the original method shorter and easier to understand.

• Replace Magic Number with Symbolic Constant: Find any raw, unexplained numbers in your code (e.g., if (user.role == 3)) and replace them with a named constant (e.g., if (user.role == ADMIN_ROLE)). This makes the code self-documenting.

• Replace Nested Conditional with Guard Clauses: Instead of deeply nesting if statements, check for all the error conditions or edge cases at the very beginning of a function and return early. This flattens the code and makes the main, “happy path” logic easier to read.

Macro-Level Fixes: Architectural Modernization

For systemic issues like a monolith, you need architectural patterns, like the Strangler Fig Pattern. This is the best pattern for incrementally replacing a legacy system. You build new functionality as separate services and place a routing layer in front of the old monolith. Over time, the new services “strangle” the old system until it has no responsibilities left and can be safely left. This way you avoid a high-risk “big bang” and can deliver value incrementally.

6. How to manage and prevent technical debt?

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Prevention is always cheaper than remediation, so these guardrails will help you save both your nervous system and project’s budget.

1. Automate Quality Gates: Integrate static analysis and testing into your CI/CD pipeline. Quality Gate is an automated check that fails the build if it doesn’t meet quality criteria, like minimum test coverage or zero new critical bugs. This makes quality non-negotiable.

2. Adopt the “Boy Scout Rule”: Be a good scout and “always leave the code you’re editing a little better than you found it”.

3. Modernize with Infrastructure as Code (IaC): Manage servers, databases, and networks as code using tools like Terraform or CloudFormation. This keeps environments consistent, repeatable, and under version control.

4. Foster Psychological Safety: Create a culture where developers can speak up, ask questions, and push for better practices without fear. If mistakes get punished, people just get better at hiding them – and hidden bugs age like milk, not wine.

Conclusion

Technical debt is inevitable, but it is controllable. Classify debt, make it visible with data, prioritize by impact, and fix it in safe steps to regain control.

Ultimately, managing technical debt is a reflection of your team’s culture. The best strategy is prevention, but if it didn’t work for you, get in touch with us. We help companies get rid of legacy code. 

Find & Fix Technical Debt: FAQ