Evolution of the Pyramid with the Three R's

Coupa Engineering has reaped tremendous benefits from integrating automation into the testing strategy, resulting in reduced effort and timelines for delivering a higher-quality product. These advantages stem from Coupa's top-down transformation approach based on the “Three R” pillars of Reliability, Repeatability & Reusability, thereby increasing quality, productivity & cost optimization.

The primary benefits of automation, including test reusability, expanded test coverage, and earlier feedback and bug detection, are driving engineers and organizations to shift away from manual efforts. Automation surpasses manual testing by simulating simultaneous users and requests on applications, including calls from various platforms and devices, which is nearly impossible to achieve manually. However, this transition is not an overnight task, as engineers need to overcome numerous challenges, from designing a strategy to acquiring the necessary knowledge, skillsets, and tools.

Coupa’s Top-Down Transformation Approach

Coupa Quality Engineering took this challenge and evolved a transformation approach based on the “Three R” pillars. As depicted below, with each transformation in our Top-Down Approach, we encapsulate benefits of the previous stage along with additional benefits derived from the transition stage, thereby making it a more and more effective and efficient approach to follow-on.

Starting at the top with manual testing which covers test cases to a certain extent with manual efforts involved
Adding on with our automation framework, adding robustness to expand test cases even further
Using sanitized production data for a more real-life test widens the effectiveness to and allows for continuous integration and delivery
Adding containers to increase efficiency and allows for tests to be more widespread
In the future, adding AI to create autonomous testing will make the tests even more robust.

As tools and technologies have evolved, so have skillsets and expertise to access these tools. With this, engineers were able to overcome the challenges faced in manual testing by designing and developing an Automation Strategy and Framework and making it robust by refining it over time. Engineers are well-versed with the transformation from manual efforts to a more robust automation framework. But the main challenge does not lie here.

Synthetic Testing With Sanitized Production Data

Another area of concern in delivering high-quality products involves the use of realistic data and scenarios for product certification. Synthetic data falls short in uncovering real-world data issues and edge cases observed in production. Aligning the test environment with production by copying production data presents complexities such as snapshotting, data masking, and ensuring data security and privacy compliance.

Coupa engineers have developed a framework to address these challenges, mimicking production data and scenarios to optimize the product and automate the discovery of edge cases. The framework includes two interconnected sections: Data Capture & Replay, and Production Data Copying, enabling the extraction, refinement, and secure usage of test data and scenarios. The Data Capture and Replay section captures end-user events from sources like application logs and performance monitoring tools, then processes the data through a series of engines including Parsing, Mapping, Script Framework, Scenario Generator, Execution, and Reporting Engines. The Production Data Copying section involves modules and drivers that snapshot and sanitize production data for use in test environments. This comprehensive framework facilitates the extraction, refinement, and utilization of test data and scenarios, as well as the secure and protected copying of production data for testing purposes.

Containerizing

As businesses adopt DevOps for continuous integration and delivery, the need for continuous testing is paramount. To reduce the cost of maintaining separate infrastructure, Coupa Quality Engineers developed a Containerized Continuous Delivery & Testing Framework. This framework enables on-demand execution of automation tests using application containers like Docker.

The Future

As technology advances more and more, an era will soon approach where the norm of ‘Self Discovering Autonomous Testing’ will make a buzz, where systems will identify and create required test suites and data without manual intervention. This approach will have key benefits of self-healing and smarter resources as test suites and data is being generated automatically with no or minimum skill set or expertise. Much thought, design and conversation will be required before this can happen.

Author’s Bio

Lokesh Gulechha, a Lead Performance Engineer based out of Pune, India, has worked at Coupa since 2020. He consistently develops and implements innovative ideas which transform business operations, enable dramatic quality improvement, increase productivity and reduce operational costs. He believes in using disruptive innovation and transformation in the technology space to enhance enterprise business. Lokesh is the author of several publications and frequently speaks at conferences and training sessions to aid others in using tech to transform business operations.

If this sounds like interesting Engineering problems you’d love to help revolutionize with us at Coupa, visit our careers page.

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