Software development is a complex task, especially when dealing with an intangible product based on logic and with various ramifications. Often, those unfamiliar with this process tend to simplify it and underestimate the effort required to perform certain tasks, which is only understandable to those involved or experienced with IT projects and comprehend the work necessary to produce high-quality software.
This complexity frequently puts the IT department in a chase after business needs, trying to keep up with requests and logic changes imposed by strategic decisions in managing departments and organizations. Developing software, regardless of its nature—be it automation, integration, a web page, or even a game—requires adherence to a set of methodologies to ensure a quality delivery aligned with expectations, in addition to a team capable of architecting and developing high-quality code while accurately interpreting business requirements.
When it comes to the development of RPA – Robotic Process Automation, that is, sequences of actions that allow machines to replicate human behavior in repetitive processes, freeing them to dedicate themselves to tasks of greater value to the business and better time management, code review is often overlooked due to the nature of the platforms used. This review is crucial, especially in teams with less experience. Since most RPA platforms are low code, making the code review process subjective and prone to errors.
Due to this low-code nature, it is also challenging to use code repositories like GIT and view changes in the form of Pull Requests. It is equally difficult to apply static code analysis tools, which analyze metrics and issues in the code and track its evolution. Although some platforms strive to implement automatic and unit tests, they are not always easy to create and execute.
Facing these challenges and based on conversations with clients and partners, we have noticed a significant increase in automations performed in Python or other programming languages. This feedback, combined with our experience, indicates that such process automations tend to be more stable, requiring less future maintenance. We believe this is partly due to the quality of the code produced and the attention developers and engineers pay to creating sustainable, secure, and scalable code. Licensing issues and sustainable scalability are also leading many organizations to rethink the application of low-code platforms.
While automations based on programming languages may lose some of the initial speed and the ability to quickly reassign resources, our experience shows that, in most cases, these advantages are quickly surpassed.
The code review process in RPA projects plays a fundamental role in ensuring the quality, sustainability, and security of automated solutions. Transitioning to automations developed with conventional programming languages, although it may seem challenging at first, offers significant advantages in terms of stability and long-term maintenance. For organizations, adopting rigorous code review practices and exploring alternatives to low-code platforms not only improves operational efficiency but also strengthens innovation capacity, ensuring that process automation strategically aligns with business objectives and effectively contributes to growth and adaptability in the constantly changing business environment.
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