Case Study

Evolving a Fragile Test Framework for Scalable and Maintainable Systems


Client Background

A growing software company had reached a critical point where their development team faced escalating issues with their test framework. As the application scaled, the test code had grown organically without evolving its underlying structure. Initially, the framework was simple, but over time, the lack of deliberate design decisions resulted in a fragile, complex, and function-based test framework. Written in TypeScript, it had become difficult to maintain, extend, and modify. The team was struggling to address the increasing technical debt and was finding it difficult to onboard new developers and testers.

Challenges

Fragile Test Code The framework was prone to frequent breakages when new features were added or when test cases were refactored.
Complexity The existing test code had grown overly complex due to tightly coupled functions, making it hard to debug and extend.
Cognitive Overload Testers found it difficult to understand the test code and apply consistent patterns, leading to inconsistent test quality and increased risk of undetected issues.
Tech Debt Due to the ad hoc growth of the framework, the team was accruing significant technical debt, which hindered their ability to adopt modern practices and scale their testing efforts.

Igenium Labs Approach

1. Modern Design Practices

Igenium Labs started by evaluating the current framework and identifying areas where modern design patterns could be applied. The goal was to refactor the code to reduce cognitive load and ensure that the framework could scale as the product evolved. The solution focused on applying principles of Object-Oriented Programming (OOP), Dependency Injection (DI), and design patterns like factories, builders, and validators.

2. Refactoring the Framework

The first step was to decouple the function-based approach and introduce classes, which could be instantiated and used across different parts of the test suite. Key changes included:

Factory Pattern A factory was introduced to handle object creation, ensuring that the test components could be created with different configurations as needed. This helped reduce redundant code and allowed for easier test data setup.
Builder Pattern The builder pattern was employed to allow testers to construct complex test cases step by step, enabling them to easily modify and extend tests without directly altering the core framework.
Validator Pattern A validator pattern was introduced to check the integrity and correctness of data, ensuring that tests were not just executed, but also validated against expected outcomes consistently.
3. Training Testers

Alongside the technical refactoring, Igenium Labs helped the client's testers understand how to leverage the new patterns effectively. This was done through:

Workshops

Training sessions were held to teach the testers the concepts of OOP, DI, and when to use design patterns like factories, builders, and validators. Emphasis was placed on reducing cognitive load by adhering to these patterns.

Integration of GenAI

As part of the training, testers were introduced to generative AI (genAI) tools that helped them auto-generate repetitive test data or scaffold test cases. Testers were shown how to use genAI as a tool to accelerate test creation, while still adhering to the best practices in design patterns.

Practical Usage

The testers were taught how to use factories for creating test objects, how to apply DI to inject dependencies, and how to structure tests to remain scalable and maintainable.

4. Reduced Complexity and Increased Maintainability

After the refactor, the test framework was significantly more modular. The use of OOP allowed components to be reused and tested in isolation. The builder pattern made it easy to modify existing tests, and the validator pattern ensured data integrity. The adoption of factories and DI improved flexibility, as new configurations could be added without modifying existing code.

The overall cognitive load for testers decreased, as they no longer needed to worry about managing complex and fragile test setups. Instead, they could focus on writing meaningful test cases and rely on the framework to handle the underlying complexity.


Results

Reduced Tech Debt

The client was able to address significant technical debt by refactoring their test framework to use modern design practices, making it easier to maintain and extend.

Improved Productivity

Testers could work more efficiently, using design patterns and genAI to streamline their work. The new approach reduced time spent on test setup and debugging, allowing testers to focus on creating high-quality test cases.

Scalability

As the client’s application continued to grow, the new test framework scaled with it. The modular approach, combined with the use of factories and DI, meant that adding new tests or modifying existing ones could be done without disrupting the core framework.

Better Onboarding

New testers and developers were able to quickly get up to speed with the new test framework due to the clear, modular structure and the comprehensive training provided.


Conclusion

By applying modern design practices and introducing tools like genAI, Igenium Labs helped the client evolve their test framework from a fragile, function-based structure into a scalable, maintainable system. The refactor reduced cognitive load for testers, improved productivity, and set the foundation for a robust testing process that could evolve alongside the growing application. This case highlights the importance of evolving test frameworks alongside application growth to avoid technical debt and ensure sustainable software development practices.