Are we testing wrong? Or coding wrong? Or planning wrong? Worse: are we getting everything wrong?
What's the real advantage of adopting a microservices architecture or a segmented system if every software change automatically triggers a regression test request? Is this due to a legitimate fear of system impact? If so, are we truly refining and analyzing these impacts correctly before implementing changes? Or has this simply become a convention we follow without questioning?
Regardless of the reason, it's the QA's role to question it. We must evaluate whether regression testing is genuinely necessary in all situations and propose more precise alternatives with a higher probability of ensuring software quality. Regression testing should be an exception, not the rule.
The Cost (and Risk) of Regression Testing
Regression testing is costly - whether done manually or automated.
For manual tests, depending on the size and complexity of the software, we're talking about hours or even days of work. Yet, even then, there's no guarantee of adequate test coverage. Some parts of the system may remain untested, allowing defects to go unnoticed.
In automated tests, the scenario can be similar. It's common practice to focus on main flows and critical functionalities, prioritizing what seems most relevant. However, this can leave significant gaps, compromising the overall reliability of the tests.
Furthermore, pursuing the idea of automating every flow, interaction, and exception in the software can lead to chaos.
Imagine a scenario where the test codebase surpasses the application's codebase in size. Maintaining this level of automation could become more expensive than evolving the software itself. Testing should add value, not become a bottleneck.
Requesting regression tests for every change is like using a hammer to fix every problem. It's not always the right tool for the job.
How to Reduce Dependency on Regression Testing
Honestly, there's no single or definitive answer to this question. However, some practices, when applied correctly, can help reduce the excessive reliance on regression testing while increasing confidence in the software.
1. Sound Architectural Practices
The system's architecture is the foundation. In modern architectures like microservices, it's crucial to clearly define the boundaries of each module and ensure their responsibilities are well-delimited.
2. Effective Unit and Integration Tests
Unit tests are the first line of defense. They ensure that each code unit functions as expected.
Integration tests, in turn, validate whether the microservice interacts correctly with real dependencies (RabbitMQ, databases, external APIs). This reduces the need for broad regression tests by confirming the service's behavior in scenarios close to production.
3. Strategic Test Planning
QA needs to invest more time in impact analysis. Software changes rarely affect the entire system. Understanding where the real impacts are is essential for planning more focused and relevant tests.
Two approaches can help structure this planning more strategically:
- Shift-Left Testing
This practice emphasizes prioritizing quality from the earliest stages of the development cycle. Unit, integration, and contract tests are executed as early as possible, in parallel with development, reducing the risk of accumulated issues that require extensive regression tests later. This also fosters a culture of collaboration between development and QA, enabling early identification of risks.
- Risk-Based Testing
This strategy focuses on prioritizing areas of the system most likely to fail or with the greatest potential impact if something goes wrong. QA identifies critical functionalities, analyzes the risks associated with each change, and directs testing efforts to the areas that matter most. This allows for smarter coverage, minimizing the need to validate the entire system with regression tests.
How These Practices Help:
With shift-left testing, many problems are identified and fixed before reaching the integration stage, reducing the need for late-stage validations.
Risk-based testing ensures time and resources are spent where they truly make a difference, avoiding unnecessary effort in low-impact areas.
4. Automation Aligned with Business Goals
Automation should be strategic. Not everything needs to be automated, but what is automated should be carefully chosen. Prioritize critical scenarios and those that add real value to the business. Automating indiscriminately only increases costs and complexity.
5. Monitoring in Production
Modern tools allow for monitoring software in production, identifying real usage problems that tests might not foresee. This continuous feedback complements testing and reduces the need for extensive regression suites.
Shifting Focus: Intelligent Quality
Regression tests are often used as a safety net to compensate for deficiencies in other areas, such as planning, architecture, or development. They still have their place. In large-scale changes, such as extensive refactoring or critical updates, regression tests may be necessary to validate overall stability. However, they should be the exception, not the rule.
Testing what truly matters is more important than attempting to test everything. This requires a joint effort between development, QA, and architecture to create more resilient systems and eliminate blind spots in the development cycle.
In the end, quality is not just about testing. It's about strategically thinking ahead to prevent failures before they even exist.
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