RPA QA relies on more than just testing new bots before software goes live. “Bot management is an ongoing dance with the full ecosystem surrounding a process, in comparison to building a modular component within that process,” Cottongim said.
To create a healthy, reliable, and productive staff of RPA bots, software testers need to know what causes failures and inherent weaknesses in RPA, and the right workflow for RPA QA — particularly RPA bots. Ongoing quality comes down to the development team approach as well as smart monitoring in production.
How RPA bots fail
Bots have seemingly innumerable ways to fail. However, the root of the problem is almost always a lack of human communication, Cottongim said. Static bots and dynamic humans are a dangerous mix for RPA QA.
For example, a worker might change an SAP report without knowing a bot relies on the program to complete an automation sequence.
Why RPA bots don’t like change
For QA, RPA developers should incorporate variables into the script that ensure bots adjust to changes in the path. But to eliminate this inherent weakness, developers would have to predict every possible variation. Examples of how a bot could break include:
- Change in UI from plugins, patches, browser upgrade or screen resolution reset;
- Bot control room restart;
- Bot services restart;
- Database maintenance;
- System maintenance;
- Expired credentials; and
- Application maintenance.
What RPA QA workflows look like
Kalokhe at Saggezza offers these ways to maintain bot quality once deployed:
- Analyze the error rates, to prioritize and guide revisions.
- Regularly monitor the bot performance success rate.
- Implement bot optimization practices using metrics like average process handling time and turnaround time.
- Evaluate key performance indicators in a monthly review.
- Dedicate a team member to monitor the error logs and investigate issues.