Why 100 Percent Test Coverage is Not Possible — Lessons from Testing Banking and Healthcare Systems
\ The pressure of "am I doing enough" and "have I tested enough" is compounded by the looming release date, which cannot be moved, and a regression test suite that continues to grow, the feeling of doubt every QA engineer gets at least once, and finally, the big thought of “ in this new release what if I miss something important?"
Early in my career, I thought the big answer to these thoughts was simply "Add More Tests." And eventually, we should strive for full coverage. After all, there are no untested paths.
However, when I began working on banking and healthcare systems, that philosophy did not last long.
In banking and healthcare systems where real money moves and real patient data are used, I learned something very quickly: 100% test coverage does not equal real confidence. In plain language, it did not work.
The Illusion of Coverage in High-Risk Systems
Covering the entire application with test cases and automation may look reassuring on paper; however, modern systems are so complex that coverage metrics do not give the complete picture.
Banking platform flows include:
- Many transaction paths.
- Multiple external payment providers.
- Very strict security and compliance requirements.
Healthcare systems also include:
- Sensitive patient data.
- Role-based access to the system.
- Complex workflows that span multiple teams and systems.
Even though you can have thousands of automated tests pass, you can still miss the most critical failure scenario. I've seen systems with "excellent" coverage fail due to a lack of thoroughness in testing a high-risk path, or to subtle omissions of a low-risk path.
At that point, it was apparent to me that coverage numbers do not measure risk. A test suite with 100 passes does not guarantee the application's 100% effectiveness.
What Experienced QA Engineers Focus On Instead
As QA engineers gain experience, the job, aims, and scope become clearer. It's no longer about running as many tests as you can, but about identifying where failure would have the most significant impact.
In highly regulated environments, every decision is weighted with consequence. A bug in a banking flow can negatively affect the company and customer trust and compliance. A defect in healthcare software can cause delays in care or expose patient data. This is why Risk-Based Testing (RBT) is necessary, a practical survival skill.
Risk-Based Testing is much more focused on making practical choices under pressure than in theory.
When timelines are short, release dates knocking on the door, which in most cases they almost always are, paying more attention to key areas of the application that matter most is wisdom.
1. Core Business Logic
Banking:
- Payment process flow: the customer uses the application to send out payments, pay bills, etc.
- Transfer Funds could entail sending out money.
- Post the Transaction correctly, and the account balance syncs properly. APIs, ATM machines, Atm matchines, etc.
Healthcare:
- Record Patient Data
- Send Clinical Information
- Initiate Downstream Workflows.
If the main structure of the application fails, the system will definitely fail. No matter how beautiful or polished the front office is. The system's primary paths deserve the most thorough testing. This could be done manually or using automated testing.
2. Authentication, Authorization, and Security
Access control is not optional in regulated industries. Industries like banking, testing essential flows like the Login functionality, payment sending and receiving, and load testing the application are always crucial.
Example of areas I prioritize
- Login flows.
- Permission.
- Role-based access.
- Injections
Small mistakes here are not just bugs; they can become security incidents that affect credibility and security, and can also affect the company's continuity, either positively or negatively. These areas need to be carefully validated, especially when changes occur.
3. Data Integrity and Consistency
Some of the most significant bugs I have experienced were not visible at the surface level.
The UI looked good, the workflow worked out; however, the underlying data told a completely different story. Data integrity is critical in banking and healthcare systems. Ensuring that data is created successfully, can be modified, and stored accurately without duplication or corruption.
4. Critical Integrations
Most real-world systems do not operate independently; microservices, Payment gateways, third-party APIs, reporting systems, and other external services all pose risks. What I have learnt over time is to treat integration points as first-class citizens in testing, since if an integration fails, the entire system will usually fail as well. A practical example was an application I worked on; the application itself did well under stress test, but failed to consider a stress test on the third-party integration endpoint, which actually caused a major delay to the company's application during the peak period. This would have been noticed if more attention had been placed on critical integrations
5. Recent and High-Risk Changes
If I am limited by time, I always ask: What changed recently? This is a big question QA Engineers should always ask. Changes in features, refactorings, and configuration changes are generally where problems arise. Focusing your testing efforts on these areas will generally yield better results than spreading your efforts over the entire system.
Why This Method Increases Quality — and Reduces Anxiety
After I stopped trying to achieve 100 percent coverage and shifted toward a focus on risk, things began to shift, the application became more stable, and i could detect were major issues could arise based when we have a new feature added to the application, or a code refactoring etc. A picture image is to ensure a break in front of the outside, just lock the doors and windows, safety can skyrocket up to 60%, although other factors also need to be considered.
With this, I got more stable results with my test application, and testing became more thoughtful. releasing the product felt more manageable, my constant background worry disappeared. Risk-based testing creates alignment between QA and business reality. Risk-based testing allows teams to make informed trade-off decisions rather than pretend everything can be tested equally.
Conclusion
Quality is not about testing everything; quality is about testing what is most important — especially when the consequences of failure are severe. In banking and healthcare systems or any other application, be it web, mobile, software, hardware, this thought process on how to approach testing an application is not merely helpful; it is necessary. When QA decisions are driven by risk rather than coverage metrics, teams can deliver with increased confidence even under intense pressure.
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