Hyperautomation — are we there yet? No expert can say with absolute certainty at what juncture we will enter this exciting chapter. Just like the Industrial Revolution, hyperautomation is a constant transition to better manufacturing and clerical processes using technology — not a specific tipping point.

Nevertheless, once we get there, if we haven’t already, robotic process automation (RPA) will have played an important role in this journey.

To offer some context, Gartner describes RPA as the fastest-growing segment of the global enterprise software market after advancing 63.1% in 2018 to $846 million. In 2019, it estimated that the RPA revenue would reach $1.3 billion.

The primary reason behind RPA’s growing popularity is its ability to help organizations with legacy systems remain competitive by automating their workflow. By workflow I mean a deluge of repetitive activities requiring low cognitive effort, including many that are performed during software testing.

RPA is such a power tool that it’s already replacing regression, performance and load testing. As a result, QA professionals are at liberty to channel their efforts on mentally stimulating activities such as exploratory, usability and ad hoc testing.

For those still confused about RPA, here’s an abbreviated definition: It’s an automation tool native to the AI habitat that automates a task by watching the user perform it in the application’s graphical user interface. This is what makes RPA so appealing: It enables codeless testing that, as you’ll discover below, will impact an even wider scope of testing domains in the future.

RPA booms in acceptance testing of large-scale systems

As pointed out by the authors of this 2019 research paper, the unique versatility of RPA tools allows testers to save resources on a number of time-guzzling activities. Think test data preparation and setting up of preconditions to ensure that the application meets all requirement specifications. The preconditions are numerous, ranging from resetting the application state, checking that the test environment has been properly configured or that a process for managing identified defects is in place. That’s not all — testers can also use RPA in regression tests and to check post-testing conditions.

Imagine how much time and resources large enterprises will save using RPA to test their applications — especially those relying on outdated software. The paper’s authors hit upon something else: They identified several components of RPA tools that, I believe, a growing number of large-scale systems are likely to formalize in the future:

• Design studio: It acts as a process design environment or description manual of executable code, including process steps, rules and procedures for accessing large, integrated systems. These items can be automated recordings of user actions or programming language to create the steps.

• Process execution environment: This is where the user (a schedule, event or another bot) starts the work of the robot, which can occur on a dedicated or virtual server.

• Management environment: The industrial application of RPA in any large organization involves a simultaneous execution of countless robotic processes. The management environment, or the system’s IQ, is required for seamless coordination and control of these processes.

• Process analysis environment: This is for providing reporting and visualization of the status of all robots.

Outsourcing wanes as a major cost-optimization factor

Although cost optimization is still considered an important criterion for outsourcing, it’s no longer at the top of the enterprise’s list, or even in the top five, according to the Deloitte 2018 Global Outsourcing Survey (download required). Setting up offshore offices just isn’t the silver bullet for cost savings as it once was — transformative technology solutions are.

Rising wages in the emerging economies coupled with technology advances such as RPA tools can affect offshore operations, which have been around since the 1970s. Most respondents in the Deloitte survey acknowledged they should change their outsourcing strategy in favor of disruptive solutions, while 72% are adopting or considering adopting RPA solutions.

RPA expands in business process outsourcing projects

In the traditional software life cycle, testing is performed in a testing environment before deployment in the production environment. But what happens when the testing environment isn’t available? This is the case with many business process outsourcing (BPO) projects such as HR, accounting and customer relations, which are contracted to third-party providers. As suggested by the writers of the research paper “Toward a Method for Automated Testing in Robotic Process Automation Projects,” RPA can generate a testing environment and a test case by monitoring the activities of the humans whose processes are to be robotized. The screen captures mouse and key actions, enabling RPA to mimic the real environment and then generate a test environment as a fake application.

RPA-based load modeling replaces traditional performance workload distribution

When testers conduct their software requirement analysis for predicted load, they usually talk to the client about the system’s user base, critical business transactions and expected response times. The trouble is, it’s often hard to get concrete answers to these queries, which can vary from one person to another.

As Tirthankar Sengupta reveals in his paper “Robotic Process Automation in Software Performance Testing Workload Modeling,” this method is also time-consuming and prone to human error, and it can vary between industries and business domains. Sometimes the stakeholders don’t even have sufficient information about nonfunctional specifications such as performance metrics.

In this case, the system logs must be analyzed to retrieve that information: the number of users logged in per hour, top methods which are called frequently, etc. Rather than rely on assumption, word of mouth and intuition, testers can send clients a questionnaire that captures workload planning information using RPA or the user interface path. Once they obtain the information, they can easily construct profiles for use in performance testing planning and execution.

Are you hyperautomation-ready?

Enterprises should start bringing RPA into the testing fold if they plan to save resources, reduce defects and prepare for a future that is already closer than we think.

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