Test Automation Vs. Intelligent Test Automation and Should You Make the Shift?

The role of automation in the evolution of software testing
I’ve managed quality testing projects for over 18 years now, and I can testify to the fact that test automation has been a key pillar of software testing for over a decade now.

It has been proven beyond a doubt, that test automation provides an impressive return on initial investment, in terms of lowered costs, better product quality, quicker time-to-market, reduced effort, increased efficiency, and fewer errors. This has led to its ubiquitous adoption around the world and has majorly contributed to the evolution of software testing to what I call software testing 2.0, or Quality Engineering (QE). There is no debate – test automation has effectively addressed the pain points and inefficiencies of manually performed regression testing, end-to-end functional testing, and test data conditioning. It’s here to stay.

Now the question is, can test automation be improved and can stakeholders get even more out of test automation? The answer is, yes, to both questions, with intelligent test automation, which is the evolution of traditional test automation, a key pillar of what I foresee as software testing 3.0, aka, Intelligent Quality Engineering (IQE).

What is intelligent test automation?

Let’s delve deeper into the current test automation landscape, see what it offers, and compare it with intelligent test automation. Tools categorized as intelligent test automation tools use technologies such as Robotic Process Automation (RPA) or methodologies such as model-based testing. For instance, UiPath Studio Pro is an RPA tool for test automation and Tosca is a model-based testing tool.

Let’s see how traditional test automation tools compare with intelligent test automation tools, based on a comparative study that we executed.

Here’s a summary of what we learned:

Our findings certainly seem to tip the balance in favor of intelligent test automation tools. But let’s explore in more detail, the four factors that measure the success of any automation testing tool or method and the maturity of the testing itself. These are:

• Applications coverage
• Automation efficiency and scalability
• Ease and efficiency of maintenance
• Security considerations

Applications coverage:

Traditional test automation tools: When selecting traditional test automation tools, there are industry leaders for the type of application under test (AUT). Selenium, for instance, is one of the first choices for web automation in many tool-evaluation rounds. However, this has compatibility issues if used for desktop applications. Similarly, some preferred tools for desktop automation may not be the best fit for web app automation testing.

Intelligent test automation tools: A single tool can possibly be used for test automation across applications, including desktop, web, mobile, and even APIs. Such extensive coverage makes these tools strong candidates for consideration when there are multiple applications and platforms in a business application landscape.

Automation efficiency and scalability:

Traditional test automation tools: Coding languages like Java or VBScript are used to build test automation scripts. The scripting efficiency is therefore proportional to the technical proficiency of the automation developers. Effective use of these tools also depends on the availability of resources with specific technology skills.

Intelligent test automation tools: Most intelligent test automation tools take a scriptless automation approach. This is either by sequencing predefined library functions in the form of a visually verifiable flow, or by using model-based testing concepts, scanning the applications under test to create test models. Since no coding is required, there are benefits in terms of increased productivity and time & effort efficiencies. Even business stakeholders and non-technical resources can handle these tools with a bit of training. Increased script handling efficiencies with provisions for rule-based testing and unattended test execution are other popular features of intelligent test automation tools.

Ease and efficiency of maintenance

Traditional test automation tools: The need for coding and skilled resources leads to maintenance being more time consuming and effort intensive.

Intelligent test automation tools: Lower effort is required to maintain test automation when applications change due to modified business functions or organic growth in the business landscape – some of this is already factored into the initial automation build.

Security considerations

Traditional test automation tools: In most of these tools, security passwords are stored on Excel files and called from there.

Intelligent test automation tools: These tools have strong security provisions such as password encryption, role-based access controls, and so on.

Find out if your business is ready to take the intelligent test automation leap

While the efficiency data points and features available within intelligent automation tools may make them the overwhelming favorite in tool evaluation rounds, does that mean intelligent automation tools are the answer for any test automation needs going forward? Not really! This decision is dependent on several factors. First ask these questions:

• Does your business landscape have complex and multiple application coverage?
• Is consistent scalability of the application under test expected?
• Is extensive automation coverage across applications required?
• Is the efficiency of the current automation build a deterrent to increasing automation coverage?
• Can a new automation tool co-exist with the current automation suite?

If you answered “yes” to most of these questions, then you may have a solid business case for using intelligent test automation tools. But, if your business has already built a sizeable and optimized automation artifact on traditional tools, you may have to defer your decision. In conclusion, rather than taking a tactical decision that brings only short-term benefits, I recommend taking a strategic decision on whether to continue using traditional test automation tools, switch to intelligent test automation, or utilize a combination of both tool types, for long-term benefits.

Rejin Chandran heads the Intelligent Automation practice and QE Center of Excellence in the Synechron Payments business division. He has over 18 years of experience in the software industry and has worn many hats in multiple roles across software development, testing, and automation. His responsibilities include providing solutions and strategies related to delivery incubation & delivery management, business solutioning, charting roadmaps for his practice areas in line with the company’s strategy, capability building, handling partnerships & alliances, and capacity management.

If you have any questions on automation or quality testing services, you can email rejin.chandran@synechron.com