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Case Study 2: Regression Testing as a Service (RTaaS) for SaaS Platform

Updated: May 1

Background: A SaaS (Software as a Service) provider offered its clients a comprehensive business management platform.

With a multi-tenant architecture and continuous updates based on user feedback, ensuring backward compatibility and stability was a formidable challenge.

Challenges: Frequent updates and releases required extensive regression testing to cover various use cases, data sets, and integration points. Automated Testing limitations were another challenge because it does not cover all edge cases. Manual testers were required to ensure backward compatibility and stability even though Automated Testing helped with repetitive areas.

CI/CD pipeline had broken due to changes in code, and dependencies. Therefore, maintaining a stable pipeline and quickly resolving issues requires a proactive approach. While the QA team regularly updated and expanded test suites to cover new features and edge cases, the Dev team made some improvements from their end for version controlling and branching. Apart from that, Root Cause Analysis was another good thing the team did to identify underlying causes and prevent similar problems in the future.

However, the below points were not among our challenges. Oh yes...

- User and Client Dependencies such as having a diverse user base using various software versions.

- Client customizations with customized implementations based on specific versions.

Strategy: The testing team introduced Regression Testing as a Service (RTaaS), offering a dedicated regression testing framework that seamlessly integrated with the SaaS platform's release cycle. Clients could opt-in to scheduled regression testing cycles or trigger ad-hoc regression tests before major updates.

  • Understand the SaaS Platform Structure:

- Identify the architecture, APIs, and data flows within the SaaS platform.

- Understand the user journeys and critical functionalities that require regression testing.

  • Define Regression Testing Scope and Objectives:

- Determine which tests should be included in regression testing (e.g., critical business functions, integrations, security features).

- Set objectives such as minimizing test coverage gaps, reducing test cycle time, and ensuring stable platform functionality.

  • Choose a Test Automation Framework:

- Select a robust test automation framework that supports the programming languages and technologies used in the SaaS platform.

- The framework includes Selenium and TestNG.

  • Design Test Suites for Regression:

- Create modular test suites that focus on different parts of the SaaS platform (e.g., frontend, backend, APIs).

- Include both positive and negative test cases to cover various scenarios.

  • Implement Continuous Integration and Continuous Deployment (CI/CD):

- Integrate regression tests into the CI/CD pipeline to ensure automated and consistent testing with every code change.

- Tools like Jenkins, GitLab CI, or GitHub Actions can be used for CI/CD automation.

  • Use Cloud Infrastructure for Scalability:

- Leverage cloud-based infrastructure to run regression tests at scale, enabling faster test cycles and parallel test execution.

- Considered service Google Cloud for scalable test execution.

  • Implement Test Data Management:

- Develop a strategy for managing test data, ensuring it remains consistent and relevant across test environments.

- Consider using synthetic data to reduce dependency on production data and to address data privacy concerns.

As an example:

Generating synthetic data for a banking application involves creating artificial data that resembles real-world banking transactions, customer profiles, accounts, and other related information. The goal is to create data that has similar characteristics and patterns to actual banking data without using real customer information, ensuring privacy and security.

Tools like Mockaroo can be used for generating synthetic data with customizable fields and schema.

Create a wide range of scenarios to test different cases in the banking application. This might include:

- Different account types with varying balances.

- Diverse customer profiles with different demographics.

- Introduce edge cases and anomalies to test robustness (e.g., fraudulent transactions, accounts with multiple overdrafts).

  • Monitor and Maintain Regression Test Suites:

- Regularly update and maintain test suites to reflect changes in the SaaS platform and to address test flakiness.

- Implement test analytics to identify trends, track test results, and pinpoint areas for improvement.

Develop a dashboard to provide real-time visibility into regression test results:

Even though creating a Regression Testing Dashboard is a good strategy, it was not considered.

Implementation: Leveraging cloud-based testing infrastructure, the RTaaS platform executed regression tests in isolated environments tailored to each client's configuration. Test results and impact analysis were transparently communicated to clients, empowering them to make informed decisions about software updates.

Results: The RTaaS model provided clients with assurance of software stability and compatibility without the overhead of maintaining an extensive testing infrastructure. By outsourcing regression testing to experts, clients could focus on their core business activities while benefiting from continuous assurance of software quality. The platform's proactive approach to regression testing bolstered client trust and loyalty, driving customer retention and business growth.

In conclusion, effective regression testing strategies are indispensable for ensuring software stability amidst continuous updates. Whether adopting an agile approach, leveraging risk-based testing methodologies, or embracing innovative testing-as-a-service models, organizations can mitigate regression risks and deliver superior software experiences to users. By drawing insights from these case studies, software development teams can refine their regression testing practices and navigate the ever-changing landscape of modern software development with confidence.

Therefore, providing Regression Testing as a Service (RTaaS) allows clients to customize their regression testing based on their unique needs, business priorities, and urgent requirements.

Here are a few questions for you. You can contribute to any.

1. What advantages do you see in offering Regression Testing as a Service (RTaaS)?

2. What is your opinion on using synthetic data for regression testing? If you create your own dummy data, have you encountered any privacy issues?

I still recall the test data I used during the early days of my time as an Associate QA engineer. :D

3. What types of projects do you typically use synthetic data for?

4. What are the test strategies you have used to ensure backward compatibility and system stability?

5. What is the dashboard use used to provide real-time visibility into regression test results?

6. What are the challenges you faced with CI/CD integration?

Thanks for your time.

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