How To Perform Service Virtualization Testing The Right Way

Delivering quality software products quickly to the market is the objective that most enterprises set out for but do not quite achieve to their satisfaction. This is because, in most cases, the system components needed for end-to-end testing and integration are unavailable in the test environment. These services or dependencies such as APIs, third-party applications, and datasets, among others are often conspicuous by their absence. The reasons include the following:

• Not fully developed, evolving, or under maintenance
• Beyond the tester’s control – say developed or operated by another company, department, or process
• Do not possess accurate data to execute the required test cases
• Not fully available for testing (inconvenient time or in limited capacity)
• Difficult to provision or configure in a test environment
• Needed by various teams simultaneously for other purposes
• Costly to use for regression testing

Thus, even though the development of software products can be expedited with streamlined processes, better communication, and frequent automated testing, the wait for dependencies can throw a spanner in the works. This is because simple unit tests can be performed on sets of codes in isolation but not comprehensive testing and integration in the absence of crucial dependencies. No wonder service virtualizationhas become the buzzword for enterprises and test specialists to implement.

What is service virtualization testing?

It is a process wherein test specialists can avoid production services and use virtual services to simulate interfaces thereby accelerating testing. Service virtualization allows software testing when crucial dependencies are not available or configured for the purpose. This is done by simulating dependencies and mimicking their behavior in the test environment thereby accelerating the process of integration testing in the SDLC. Thus, key bottlenecks in the testing process are removed and the application under test is pushed forth in the production environment. Therefore, when it comes to the presence of various system components and their need to work in synchrony, a robust service virtualization strategycan fill the gap. This is done by simulating the responses or behavior of such components to ascertain how they would interact in real-time. Service virtualization testing is particularly useful when developing complex cloud-based enterprise solutions. It speeds up testing, identification of glitches, integration, and delivery of software products and services.

In the Agile/DevOps setup when there is a need to boost test automation, test specialists can undertake service virtualization implementationto aid faster testing, development, and delivery of products in a CI/CD pipeline. Thus, service virtualization can offer the following outcomes or benefits:

• A robust and comprehensive test environment mimicking an actual production environment.
• Allowing test specialists to test a software product in a simulated environment, which may be a configured product or test environment.
• Reducing the cost of testing.
• With waiting time for critical dependencies reduced, QA teams can easily analyze the behavior of such dependencies in a demo environment.
• By mimicking the actual product deployment situation the QA team can identify glitches to be experienced by actual users when the product is delivered. As a result, the actual product is remarkably robust and shorn of glitches.

How to perform service virtualization testing the right way

Given the myriad benefits of service virtualization implementation, the process should be performed meticulously.

• No need to recreate or reinvent: There is no need for a QA specialist to recreate the whole or even a portion of the component or the behavior that is being virtualized. The first step is to create a virtual asset that simulates the behavior of the component by transmitting responses to the order manager. The order manager provisions further automatically without any manual intervention thereby saving significant time.
• Test with a proper plan: While planning for a service virtualization strategy, the test cases should validate the system instead of the virtual service mimicking the dependent system. For example, the UI testing of a banking application should not be about verifying the system maintaining balance. It should be rather about verifying the transaction involving withdrawal or deposit.
• No build once and use many times: Since each team will have its own testing objective and requirement, it is better to have separate virtualization even if there is an overlap. Since a virtual service can be built quickly, the QA team can utilize its time in doing analysis rather than in implementation.
• Train the right people: Since service virtualization involves a paradigm shift in QA, it should be executed by techies rather than manual testers. This is because manual testers, in general, know the core business requirements rather than the technology to achieve the same. So, let traditional testers create test plans and leave the job of building virtual services to the techies.

Conclusion

Service virtualizationhelps developers to use their own data sets and conduct better testing before sending the codes to the test environment. This ‘shift left’ practice of testing leads to better detection of glitches early on in the development phase. The biggest advantage is about reducing the testing time in the SDLC compared to the traditional method - from weeks to days. Thus, the process delivers better quality software frequently and helps the organization gain competitive advantage.