Maintaining Code Health: Ensuring Code Quality in Test Automation

In most test automation projects, a handful of committed engineers actively dedicate their extra time or receive guidance from senior technical personnel to enhance code readability, maintainability, stability, or simplicity. Nonetheless, every software engineer plays a role in code health to some extent, as we all contribute to writing software and share a joint commitment to doing it correctly. After all, most of us do care deeply about doing it the "right way."

How can we consistently achieve this across the organization if we value coding? Standardization and Experimentation are crucial to uphold quality and nurture ongoing improvement within our testing practices organization wide.

Establishing Standard Processes

Standardization involves creating a set of practices and processes that can be replicated across internal automation frameworks and test automation scripts.  A dedicated team of engineers, serving as the core group, works to improve test engineering practices for all. This team maintains internal documentation outlining best practices and supports teams and individuals seeking guidance on enhancing practices within their projects. Additionally, the core group oversees the organization’s code review guidelines, creates internal publications detailing best practices, coordinates tech talks addressing productivity enhancements, and fosters a culture of excellence in test automation engineering.

Here are some broad guidelines that every test automation engineer should follow while scripting the automation framework and test scripts:

1. Comment your code "Properly"

Comments are crucial in comprehending and managing a codebase. However, excess of comments in code may turn into unhelpful clutter, filled with extraneous and/or outdated details.

• Write comments to explain the "why" of the code.
• Use appropriately named identifiers to guide the approach and reduce the need for comments.
• Provide API documentation to describe intended meaning and purpose, not implementation details.
• Avoid commenting about the obvious.

2. Keep the control flows "Simple"

• Avoid "too much" of nested flow. Avoid excessive nesting of flows. While the definition of "excessive" may vary, a recommended approach is to limit nesting to the second level at most and, ideally, to the third level at worst.
• Wherever "possible", move the implementation logic into methods and functions to reduce the code complexity.

3. Handle the exceptions with "Care"

While this is a topic worthy of discussion on its own, what we should bear in mind is that exception handling should not obscure the logic or attempt to catch everything. Instead, aim to catch specific exceptions whenever feasible. Avoid rethrowing a general exception without acknowledging the original one.

4. Clean it up

Applying the Boy Scout rule

"Always leave the campground cleaner than you found it," will make everyone’s life easier, whether it’s scouting camp or test automation. The idea is to keep making minor changes to the code to make it just a little bit better each time. It doesn’t mean you undertake massive code refactoring, changing something small will go a long way in keeping the code clean and maintainable for everyone on the team. As the saying goes, "A stitch in time saves nine," leaving the issues for posterity is a definite recipe for disaster in the long run. However, when doing the clean-up, ensure the testing functionality of the elements you intend to modify does not alter.

Facilitating Experimentation

While we are following guidelines across the organization to have standardization, how do we ensure we don’t stifle creativity and improvements? After all, nothing is perfect, and improvement is needed to keep up with technological changes, SDLC processes et al. Allowing experimentation will help us find innovative experiences that move the needle forward and contribute to the improvements.

Experimentation needs to be done with Velocity and Quality.

1. Experimenting with Velocity

In today’s agile world, we need to make iterative enhancements so the feedback can be plowed back into the process. Robust automation tooling is essential to expedite experimentation, empowering teams to set up, quality check, and launch their experiments effortlessly. Enhancing the existing automation frameworks using AI integrations will help speed up and stabilize the output.

2. Experimenting with Quality

It is imperative to guarantee the delivery of high-quality releases that enable us to attain definitive results, facilitating data-driven decision-making. Meticulous coordination forms the foundation of the commitment to quality experimentation. It is achieved by cultivating a culture of openness and collaboration and mitigating the impact of interactions between multiple test frameworks and plugins that could compromise the validity of results.

Conclusion

Ensuring automation code health across the organization demands a collective commitment from every automation engineer, with a few leading the charge and others contributing their bit. The balance between standardization and experimentation is crucial for fostering continuous improvement. Facilitating experimentation encourages creativity without stifling improvements. The "inspect and adapt" approach allows projects to innovate and contribute to evolving best practices.