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Test Automation and Robotic Process Automation
Exploring the differences between test automation (TA) and robotic process automation (RPA), as we head into the future in current markets, TA (test automation) and RPA (robotic process automation) operate independently of one another. In this article, we’re going to look at the differences between the two processes. This should answer questions such as:
What is robotic process automation? What is test automation? And how does robotic process automation work? What we uncover, through this, are the considerations of each and how a better, more advantageous, combined solution for businesses can exist as we move into the future.
The early introduction of test automation strategy
The test automation framework was introduced to improve the quality of our IT systems. Each change and improvement, however, required testing that added significant personnel and technical resources—delivering higher costs into the process.
This required operatives to prepare and maintain test material, and to carry out the tests. Repeating the process only added to the expense, so the idea of automating those processes and reducing their associated costs set the path in place for more beneficial automation.
What the system needed was a way to speed up testing, extend testing periods, and boost the repeatability of the processes. After a great deal of investigation, new tools were introduced to automate the testing processes.
However, testing is a complicated procedure. Software engineers revealed a selection of tests to be carried out at various points of the process, to understand where to introduce positive changes to improve performance.
Performance, ergonomics, and safety testing were relatively rare, whereas validation, regression, and integration tests, were carried out repeatedly during each session.
Those first testing tools, developed in the 1990s, are still evolving today. For years, the market was dominated by commercial solutions, yet, over the past decade, non-commercial software solutions into automated testing has driven real dynamic growth throughout the industry.
Limiting the amount of human operation during the process
Existing production staff supported the early process testing methods. Without their assistance, the updates and delivery couldn’t be guaranteed to deliver the anticipated results. With introductions into automated testing, staff involvement could be significantly reduced.
However, the production of the testing code was in the hands of the programmers, who often didn’t have the necessary expertise and knowledge of each industry. With the experienced workers being able to monitor and understand the new testing process—often via an easy-to-understand graphical interface—they could see how the results of the tests could affect their daily production.
Slowly, and purely down to the results of the new testing process, new, improved machines became part of the business operations. This was considered the introduction of RPA. However, it would be quite a while before that term would be introduced and accepted as the standard.
Why do we use framework in test automation?
Automation framework is a combination of tools and processes working together to support the testing of an application. You can see here, with the RPA and TA systems being so closely linked, how important this framework is.
The clickers that grew into RPA
These early test machines were referred to as ‘clickers’. The developers were to make dozens of these production robots during that time, and for two main reasons.
The first was that they offered swift implementation—significantly faster than the standard path via change requests in project management.
The second was the cost. Robots were considerably cheaper than changing each IT system. Where an organization already held a test automation team, they could consider the implementation of a dedicated bot to be cost-free.
How to create robotic process automation successfully?
Initially, the IT departments were skeptical. The new methods disrupted the standard processes of introducing changes. Their worries included data security issues, bot access to the company’s primary systems, faith that the machines would operate as intended en mass after the orchestration or rescaling of their production machines. It became necessary to adjust the corporate governance to include the safe functioning of robotics within the company.
Another issue was how integrating test tools might pose new threats to production systems.
Modern RPA interactivity and development
Considerable time has passed since those early testing days, and RPA, along with its new tools and dedicated ways of thinking, has added value directly to the businesses that have chosen to utilize it.
The key points still stand:
- No need to change existing systems.
- The ease of creating bots – a team member can produce robots after only a few hours of training in a dedicated studio, and without having to involve IT in the robotization process.
Until recently, this was still very much the accepted system; yet, cracks are beginning to come to light.
It appears that certain RPA implementations aren’t delivering the envisioned spectacular successes. While they may not be delivering complete failures, they are experiencing problems achieving their expected benefits.
One of the issues is down to the details in the coding process. Those writing the code need proficiency in both code and experience in the field of operation. Poorly written code creates negative implications when implemented and stabilizing bots in production. Even introducing simpler drag-and-drop code-creation systems doesn’t change the underlying code of each operation.
Performing the simplest operations, without taking into account all the operational factors, too often results in problems producing the desired quality during production.
The robots that affect change to the organization’s system are also subject to those changes in the system. The cost of implementing such changes can absorb all of the benefits of robotization if the code isn’t created correctly.
The robotization process is a software lifecycle system immersed in other processes.
- Analysis
- Design
- Coding
- Testing
- Implementation
- Stabilization
- Maintenance
The relevant IT services and technical expertise are required to fulfil each of the steps of the process. If all parts of the system operate as expected, only then will the long- and short-term benefits be realized as intended.
Interested in our solution?
Let's talkAre TA and RPA so radically different from other automated business processes?
When we look into how automation affects testing as it does other businesses’ operations, well, it isn’t too far removed. The original tester is replaced by a system, in just the same way as other work tasks will be replaced in the organization’s operation.
To create the most powerful opportunities, the robots must be tested before placed into production. The robots’ tests, therefore, need a test environment mapped from the production environment as the target area of their work.
Each robot must perform to complement the organization’s regression testing. In the same way, the automated test code written during the TA process needs to perform in a whole or as part of the robot about to be implemented in the RPA process.
In other words, both processes overlap, using each other’s resources.
Where there is a change in the process managed by the RPA, it’s necessary to incorporate it in the bots. If the TA/RPA process is created along the lines of the suggested outline, any amendment required in one particular area should replicate through all of the bots in that area. That way, standard production bots can operate in various business processes.
You can see how many similarities they hold, as shown in the following comparison:
| Requirements/features | RPA process | TA process |
| Replacing human work without the need to change existing information systems. | YES | YES |
| Operates in the initiative > analysis > cycle > designing > coding > testing > implementation > stabilization > maintenance. | YES | YES |
| Has business stakeholders, where the business is the beneficiary. | YES | YES |
| Requires the correct level of reporting. | YES | YES |
| Requires a strictly defined error/anomaly handling process. | YES | YES |
| Affects production and test systems. | YES | YES |
| Requires mechanisms for prioritizing tasks. | YES | YES |
| Requires scaling mechanisms and working in time regimes. | YES | YES |
| Requires broad mechanisms of orchestrating machines’ work, e.g., scheduling, triggers of various types, grouping, etc. | YES | YES |
| Uses dedicated technical components, e.g., database support, files, API, GUI, etc. | YES | YES |
| Requires a process-based approach to the security of sensitive data. | YES | YES |
Our conclusion
TA is a subset process of RPA. Manual testing is an area of human activity and interaction that has the potential to be automated, as many other analogue processes in so many other areas already are. However, to take advantage of the synergy provided, and each RPA robot test, we can’t treat RPA and TA separately.
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Let's talkWhat does that mean for the future?
We believe that the future will be dominated by MI/ML solutions, based on the vast data sets fed into BigData. Creating code will move to LowCode solutions, and as AI systems absorb more knowledge, their efficiency will boom.
New solutions will be able to deconstruct business processes, to find each of their optimization points, performing qualitative and quantitative analysis of the processes, and automatically generating the code to map out the process using the bot.
Our role will be reduced to merely correcting the AI system operation results and creating updates from code blocks. From there, automatic bot factories will produce sections or entire business processes, ready for implementation into their systems.