Updating Systems Nobody Understands: Your Legacy Software Recovery Plan

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At some stage, every organization running on legacy systems reaches a point where no one truly understands its internal structure and logic.

The original architects no longer work at the company. The documentation is outdated. The code “works,” but nobody can explain why and how. 

That’s where organizations realize that it’s time for modernization. However, this is often the point where modernization efforts fail. Companies rush to rewrite the code without fully understanding its pitfalls, dependencies, and hidden logic.

When there are no subject matter experts (SMEs), modernization should start with system analysis, not a rewrite. 

In this blog post, you’ll learn how to maintain and modernize a legacy system with no original developers, and don’t let outdated systems hold back your business growth.

Why legacy modernization without SMEs often fails

When SMEs leave the company, organizations lose more than just the knowledge of the legacy system’s code. They lose the context for why the system behaves the way it does.

For example, there is a brunch in the code that triggers when:

• A customer changes plans mid-billing cycle
• A payment is retried exactly three times
• An order is backdated by more than 24 hours

There are no comments or explanations for why this code was added. Without SMEs, teams can’t answer that, so they decide to just rewrite it. 

However, rewriting code without understanding the context can accumulate technical debt and reduce your system’s performance. Legacy system modernization with no documentation is challenging, and here’s why.

Behavior hidden in the database gets lost

Some business rules aren’t in the code; they result from how data is stored or updated. For example, a billing system marks an invoice as “paid” only after several related tables are updated in a specific order.

If you rewrite the code without replicating these data-driven rules exactly, the system may produce wrong invoices, assign incorrect points, or ship orders incorrectly,  even though the new code “looks correct.”

External dependencies can break things

The system often relies on processes or integrations that aren’t in the code. If you ignore them, a rewrite can silently break production. For example, the finance department generates daily revenue reports by querying live tables in a specific order. If a rewrite changes the table structure, reports fail.

Anything the system interacts with outside the visible code, such as databases, scripts, or other services, can break silently if overlooked. Rewrites that assume the code is the whole system almost always lead to such failures.

You can’t tell a bug from a requirement

When SMEs are gone, no one can verify if system behavior is intentional or accidental. Changes that seem like “improvements” can break critical processes. 

For example, a promotional discount triggers only under very specific conditions. Removing or simplifying the logic might look cleaner, but can cause customer complaints or lost revenue.

Sometimes a system has features that look unnecessary or “dead” in the code, but they serve a real purpose. A manual override is a good example: it lets a human step in and change or bypass automated behavior in specific cases.

If engineers modernizing the system see the override code, they might think it’s “dead code” and remove it. But operations teams rely on it regularly. Removing it silently breaks critical processes, even though the system still seems to run most of the time.

Without SMEs or people who understand why these exceptions exist, engineers can’t tell what’s a true bug, what’s required for compliance, or what users depend on. 

A rewrite that removes these “unnecessary” paths often introduces subtle but serious failures, such as missed revenue, incorrect reports, or compliance violations. 

In the next chapter, we’ll break down the modernization roadmap for legacy systems that reduces risks.

Modernization Risk Assessment: Map the Real System

When you don’t understand the system, the safest way to start legacy system modernization is by looking at what actually happens in production. 

Watch what runs

Look at which parts of the system are actually used. For example:

• A batch job that runs every night to recalculate balances

• An API endpoint that only triggers when a customer cancels their subscription

• A data feed from a third-party system that only comes once a month

These are easy to miss if you only read the code.

Check the logs

Logs show what happened, when, and how often. They can reveal:

• Rare conditions that still matter, like end-of-quarter reporting

• Hidden dependencies between services

Examine the database

Look at which tables and records the system reads and writes. This can uncover:

• Rules stored in data rather than code
• Scripts or manual overrides that operations run for compliance
• Records that are used in reports 

By combining these sources, you can draw a map of the system’s real behavior: what happens, when, and in what order. This map often looks very different from the code or documentation.

For example, you might see a feature that looks unused in the code, but production logs show it’s used once a month to handle special customer requests. Removing it would break a real business process.

This legacy application modernization approach provides a solid foundation for safe modernization, as you know what the system actually does, not just what the code appears to do.

Stabilize First With Characterization Tests and Capture What the System Does Today

Before you change anything, whether it’s refactoring code, moving to the cloud, or adding new features, you need to lock in how the system behaves today. This is what characterization tests do.

Without characterization tests, any change is a guess. Here is how you can make characterization tests.

Identify critical flows

Start with the parts of the system that handle money, customer data, or operational safety.

Capture inputs and outputs

For each flow, log what goes in and what comes out. Include side effects like database updates or messages sent to other systems.

Include edge cases and rare runs

Don’t ignore quarterly, end-of-month, or retry flows. They often hide critical logic.

Automate and repeat

Run these tests whenever you refactor. They act as a safety net, catching unexpected changes immediately.

Modernize in Stages: Watch First, Change Later

When modernizing a legacy system, not all code needs to be tackled at once. The smartest approach is to start with low-risk, read-only flows before touching any paths that modify data. 

This reduces the chance of breaking critical business processes while giving your team confidence in the system.

For example, a company wants to modernize its billing system. Start by migrating the monthly revenue report:

• Reproduce the report in a new framework or service

• Run it side by side with the old system

• Compare outputs for consistency

If the new system behaves differently from the old, investigate before moving on. No customer data has been changed, so the risk is low.

Use Parallel Runs and Reconciliation

Cutting over to a modernized system doesn’t have to be risky. The safest way is to run old and new systems side by side before switching users over.

How is how it works:

• Parallel runs: Send the same inputs to both systems and run them in parallel.

• Compare outputs: Check that results match exactly or understand why they don’t.

• Reconciliation checks: Compare the outputs of the old and new systems before fully switching over. 

This approach lets your team spot rare or tricky issues early, makes it easy to roll back if needed, and ensures that the new system works exactly like the old one where it matters. Users won’t notice any change, but your team will know everything is running correctly.

What You Get From a 2–3 Week System Discovery Sprint 

In just 2–3 weeks, a focused discovery sprint can give you a clear picture of your legacy system before any major changes:

• Backlog of modernization tasks — A prioritized list of what to fix, refactor, or replace first.

• Risk map – A visual or documented guide showing where hidden dependencies, risks, or fragile processes live.

This sprint highlights what really matters in the system and sets your team up to modernize safely and efficiently. You get clarity before committing to big changes, reducing bottlenecks that may appear later.

Start with a system discovery sprint to get the most out of legacy software modernization

If you want to modernize your system safely without sacrificing your business’s performance, start with a system discovery sprint.

We at Teamvoy run a 2–3 week “system discovery sprint” that includes a modernization backlog and a risk map. 

A modernization backlog includes a prioritized list of actions your team can take, such as:

• Refactoring or rewriting fragile code sections

• Replacing outdated libraries or frameworks

• Automating manual processes

• Fixing critical bugs or performance bottlenecks

A risk map is a visual or documented overview of potential problem areas, such as:

• Hidden dependencies between services or databases

• Critical edge cases that could cause failures

• Points where “temporary fixes” became permanent

• Areas with low test coverage or missing documentation

• Regulatory or business rules embedded in code or data

In just 2–3 weeks, you know what to fix first, where the risks are, and how to modernize legacy software without SMEs.

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