Every successful business eventually runs on software that was written for a different time. The system still works, customers still depend on it, but every change takes longer than it should and nobody wants to touch certain parts of the code. Knowing when to refactor legacy code, and how to do it without disrupting the business, is one of the most valuable decisions a technology leader can make.
The temptation is often to throw everything away and start again. Sometimes that is the right call, but far more often a disciplined, incremental refactoring programme delivers better results with much less risk. The key is to treat modernisation as an engineering process with clear priorities and a safety net, not as a heroic rewrite.
In this article we look at how to recognise that a system needs attention, how to choose between refactoring and rewriting, and the practical techniques we use to modernise applications safely: tests first, small steps and the strangler fig pattern.
What “legacy code” really means
Legacy code is not simply old code. Plenty of ten-year-old code is clean, well tested and easy to change. Michael Feathers, in his widely read book on the subject, famously defined legacy code as code without tests. That definition is useful because it points to the real problem: when you cannot verify behaviour automatically, every change is a gamble.
In practice, the legacy systems we encounter tend to share a few characteristics:
- Business rules are buried in large classes, stored procedures or UI event handlers rather than in clearly named, isolated components.
- The application runs on frameworks, runtimes or libraries that no longer receive security updates.
- Documentation is out of date or missing, and key knowledge lives in the heads of one or two long-serving developers.
- Deployments are manual, infrequent and stressful.
- There is little or no automated testing, so quality depends on manual checks before each release.
Refactoring, in contrast, means improving the internal structure of code without changing its external behaviour. It is not adding features and it is not fixing bugs, although it makes both of those far easier.
Warning signs it is time to refactor legacy code
Business leaders rarely see code directly, but they do see its symptoms. If several of the following sound familiar, technical debt is likely costing you more than you realise:
- Features take longer every quarter. Simple-sounding changes become multi-week projects because they touch many tightly coupled parts of the system.
- Fixes cause new bugs. Regressions appear in unrelated areas after a release, which signals hidden dependencies.
- Developers avoid certain modules. When a team says “don’t touch that”, you have a risk concentrated in one place.
- Onboarding is slow. New developers need months before they can make changes confidently.
- You cannot upgrade. The application is pinned to old versions of PHP, .NET or JavaScript libraries because upgrading breaks things.
- Scaling or migrating is blocked. The architecture makes it hard to move to the cloud, add an API or integrate with partners.
Common code smells and how they are treated
At code level, developers look for “code smells”: patterns that are not bugs in themselves but indicate deeper design problems. The table below lists the ones we encounter most often in legacy business applications.
| Code smell | What it looks like | Why it hurts | Typical refactoring |
|---|---|---|---|
| Long method | Functions running to hundreds of lines with many branches | Hard to understand, test or reuse | Extract smaller, well-named methods |
| Large class (“god object”) | One class handles data access, business rules and presentation | Every change risks side effects | Split into classes with a single responsibility |
| Duplicated code | The same logic copied across screens or services | Fixes must be applied in several places, and often are not | Consolidate into one shared function or service |
| Shotgun surgery | One business change requires edits in many files | Slow delivery, easy to miss a spot | Move related behaviour together |
| Primitive obsession | Money, IDs or statuses passed around as raw strings and numbers | Validation is scattered and inconsistent | Introduce value objects or enums |
| Hard-wired dependencies | Code creates database connections or external clients directly | Impossible to unit test in isolation | Introduce interfaces and dependency injection |
Refactor, rewrite or replace: making the call
Before committing budget, decide which of three strategies fits the system. Each has a place.
Refactor incrementally
Choose this when the system broadly does what the business needs, the core technology is still supported or can be upgraded, and the main problems are structure, testability and speed of change. Incremental refactoring delivers value continuously and keeps the business running on proven code.
Rewrite (gradually, not in one go)
A rewrite becomes reasonable when the underlying platform is a dead end, the architecture fundamentally cannot support where the business is going, or the code is so entangled that small changes are no longer feasible. Even then, we strongly prefer replacing the system piece by piece rather than in a single “big bang” cut-over. Big-bang rewrites tend to run long, because the old system keeps evolving while the new one is built, and they often miss business rules that were never written down anywhere except the old code.
Replace with an off-the-shelf product
If the legacy application handles a generic function such as payroll, basic accounting or email marketing, a mature SaaS product may serve you better than any custom code. Custom software earns its keep where it supports what makes your business different.
Tests first: building a safety net before you change anything
The single most important rule of refactoring legacy code is to get tests in place before you restructure anything. Without them, you are relying on hope.
With legacy systems, you usually start with characterisation tests. Rather than testing what the code should do, they record what it currently does. You call a piece of code with realistic inputs, capture the outputs, and assert that those outputs stay the same. If the current behaviour includes a quirk, the test captures the quirk too; whether to fix it is a separate, deliberate decision.
Practical techniques that help:
- Find seams. A seam is a place where you can change behaviour without editing the code itself, for example by passing in a dependency instead of creating it internally. Seams let you isolate code for testing.
- Test at the edges first. If unit testing is impractical, start with higher-level tests against an API or a full workflow, then add finer-grained unit tests as you break the code apart.
- Use production-like data safely. Anonymised samples of real data uncover edge cases that invented test data misses. Ensure any personal information is masked, in line with POPIA obligations.
- Automate the run. Tests that run on every commit in a CI pipeline catch regressions within minutes rather than at the next manual release.
This mirrors how we build new software: our process includes a base unit test for all logic so that future enhancements do not break the application. Bringing a legacy system up to that standard is often the most valuable outcome of a refactoring engagement. Our article on building a QA strategy with positive and negative tests goes deeper on test design.
The strangler fig pattern: modernising without a big-bang rewrite
The strangler fig pattern, named by Martin Fowler after a vine that gradually grows around a host tree, is the most reliable way we know to replace a large legacy system. Instead of switching from old to new in one go, you grow the new system around the old one until the old one can be retired.
- Put a facade in front of the legacy system. This could be an API gateway, reverse proxy or routing layer that all requests pass through.
- Pick one well-bounded capability. Choose something valuable but contained, such as customer notifications, reporting or a single product module.
- Build the new implementation alongside. Use modern architecture, clean code and full test coverage from day one.
- Route traffic gradually. Send a subset of requests or users to the new component, compare results and monitor closely.
- Retire the old code. Once nothing depends on the legacy implementation, remove it, then repeat with the next capability.
The pattern lets you deliver improvements early, reverse a step if something goes wrong, and spread investment over time. Microsoft’s Azure Architecture Center has a clear write-up of the strangler fig pattern and the considerations involved, such as keeping data consistent between old and new components during the transition.
The strangler approach also pairs naturally with moving workloads to the cloud. If infrastructure is part of your modernisation plan, see our cloud migration roadmap for Azure and AWS.
A practical refactoring plan, step by step
Here is the sequence we follow when a client asks us to modernise an existing application:
- Audit. Review the codebase, dependencies, deployment process and test coverage. Identify unsupported components and security risks first, because those carry the most urgency.
- Map business value against pain. Use version-control history to see which files change most often, then compare that with where bugs cluster. Code that is both complex and frequently changed is where refactoring pays back fastest. Stable code that nobody touches can often be left alone.
- Stabilise the pipeline. Put the code in proper version control, automate builds and deployments, and add basic monitoring so that you can see the effect of every change.
- Add characterisation tests around the high-priority areas.
- Refactor in small, reversible steps. Each change should be small enough to review in one sitting and deploy on its own. Avoid long-lived branches that drift away from the main codebase.
- Upgrade dependencies and runtimes once tests give you confidence, moving to supported versions of frameworks such as Laravel or .NET.
- Measure and report. Track lead time for changes, regression rate and deployment frequency, so stakeholders can see the investment working.
Making the business case for refactoring
Refactoring competes with new features for budget, so it needs to be framed in business terms. Avoid talking about “clean code” in the abstract. Instead, connect the work to outcomes that leadership already cares about:
- Speed: shorter lead times for the features on the roadmap.
- Risk: fewer production incidents, and removal of unsupported components that create security exposure.
- Resilience: less dependence on a single person who understands the system.
- Options: a codebase that can move to the cloud, expose APIs or support a mobile app.
A useful compromise is to allocate a consistent share of each development cycle to improving the areas you are already working in. This keeps modernisation continuous and visible without freezing feature delivery.
Our approach is rooted in precision: understand how the business thinks first, then improve the system with the attention to detail it deserves, one deliberate step at a time.
How Adriel Corp can help
Code refactoring is one of our core services. Our Code Audit & Refactoring Sprint gives you an independent assessment of your codebase, a prioritised modernisation plan and a focused sprint of hands-on improvements, including the tests that make future change safe. Whether your system is built on PHP, Laravel, .NET or Python, we can help you decide what to keep, what to refactor and what to replace, then execute it without disrupting your operations.
