RPA vs. test automation: What are the differences?

Estimated read time 5 min read


The terms test automation and RPA are often interchanged, and one might wonder if both are used for the same purposes or share the same tools. This article uncovers the misconceptions and explores the similarities, differences and possibilities of both.

Robotic Process Automation theme with hand pressing a button
Image: Tierney/Adobe Stock

Automation tools have since adopted 4.0 technologies in their evolution. Part of this adoption uses RPA, artificial intelligence and machine learning to quicken the execution of tasks in different IT branches, businesses and industries. Software testing has also experienced the use of certain automation-enhanced tools to make the work of developers seamless.

However, test automation and RPA tools — even if used interchangeably — are not the same. Understanding these differences will help involved stakeholders in companies to make informed decisions around RPA and software testing.

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What is RPA?

RPA is an acronym for Robotic Process Automation, which refers to technologies that are able to interact with tools, IT infrastructure and business processes with the help of AI and ML to learn and automate repetitive tasks. RPA is a great solution to data-intensive tasks. It can remove the repetitive human factor involved in business workflow processes by using executed commands implemented by bots to mimic human processes.

RPA helps businesses to be more compliant and audit-ready because of backlogs created from the automated process. At the same time, there is improved accuracy when repetitive tasks are freed of human intervention. This increases productivity levels of companies and allows for better recognition of opportunities and faster implementation of decisions.

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The possibility of scaling with RPA comes from end-to-end structuring which allows the bots involved to learn and interpret data for specific processes. RPA also allows the extraction of information without the need for extensive codes that can cause structural data changes. Hence it is also used for the front-end to back-end testing of applications and taught to initiate responses, trigger new functions, communicate with other systems and capture specific data.

RPA reduces the time developers spend on creating custom APIs and integration. It provides an automated management process that helps to remove the redundancy of human intervention during application testing.

What is test automation?

Test automation refers to a method in software testing that uses tools to learn, extract information and control the execution of software tests. Rather than business workflow and processes, test automation focuses on automating repetitive cases encountered during tests. No doubt, test cases become repetitive and redundant especially when working on huge IT projects. Repetition makes the software testing process more prone to errors and elongates the time spent on projects. Delivery is also poor because bugs can easily be overlooked. Most testing tools make use of AI and provide cross platforms that can allow the integration of other tools as well as enabled DevOps.

Hence test automation and RPA are similar because both are used to reduce manual repetitive processes while increasing productivity and quality of output.

What are the differences between test automation and RPA?

Differences in goal

Both processes are used for automation for different goals. Test automation is specifically used for software test automation while RPA is used for business processes which can also include software test automation. For example, in accounting, test automation can be used to automate the testing of a new application while RPA can be used to automate data entry as well as the application testing.

Differences in coding

Test automation requires a level of coding knowledge since different softwares are written with different code structures. The IT personnel can choose between VBA, JAVA, Python or other low-code and no-code platforms.

On the other hand, RPA does not require an in-depth knowledge of programming. Platforms for RPA use a visual drag-and-drop feature for the automation of tasks. However, to get into advanced business process automation, one needs to have a degree of expertise in a programming language to be able to access and manipulate base codes.

Differences in life-cycle and execution

Test automation starts from:

  • A test data management design that forms the automation framework, the test suites.
  • Then the cycle proceeds to generate test cases that are built using programming languages to execute tasks that are normally carried out by human beings.
  • With the test data obtained from the written code, smart recorders or codeless platforms, the built cases are executed to discover defects in such products.
  • If there are any errors during execution of test automation, the next phase of the cycle will involve a debugging process that can also be hastened with self-taught AI tools.
  • The concluding phrases involve analysis of results to get an overview of the tested product which then forms a report that is sent back to the development team for support and continuous maintenance.

RPA processes involves a larger scale cycle:

  • Software analyses business workflow to understand what parts of the business can be automated.
  • After determining what needs to be automated in the industry, a robot is then developed to mimic the workflow process.
  • The bot is also tested to ensure compliance and lack of errors before full implementation, support and maintenance.

Differences in scale of application

Test automation is implemented only on a small section of an enterprise for already existing software applications. Some of these small sections include research and development, quality control and IT engineering teams. RPA engulfs full departments. Not only that, it seeks to create an interlink between their processes. RPA allows data in companies to be centralized for easy access and analysis.

Both RPA and test automation are platform-independent and both seek to improve the quality of enterprise offerings. Depending on what needs to be achieved, teams can decide which to involve in their next automation project.



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