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Top 5 Test Automation Trends to Look Out for in 2024 and Beyond

Top 5 Test Automation Trends to Look Out for in 2024 and Beyond

This trend post is not like any other trend post you will come across over the next few months. You can do it and wonder what’s going on in the market for test automation services and test automation in general. Instead of much innovation from the vendors, we’re witnessing a lot of hype and marketing bluster with little tangible results.

If it’s not designed for it, it’s difficult to integrate cutting-edge technology with the current tech stack and ride the AI wave. But nobody desires to remain behind. We know that.

However, this is not a place for finger-pointing or cynicism. In 2024, there will be a lot of trends and hype. Therefore, I want to shed light on these things so you can decide for yourself whether or not they’re right for you and know the difference between marketing jargon and real information.

Let’s start with the test automation trend that GenAI is already seeing growth in.

1. GenAI in Test Automation

Nowadays, GenAI is pervasive and you can’t avoid running into it in any aspect of the software industry. We also adore GenAI. It’s excellent.

We identify two main trends. Two ways to use it now are to prompt your test steps and to generate test cases (spoiler alert: this is not the best way to use it).

They both appear to be the same at first glance. However, they aren’t. Now let’s look at two real-world examples that don’t involve testing.

Gene AI’s general use case

To create an anime drawing, you ask GenAI. Though it is generated with stable diffusion, it doesn’t seem convincing when examined more closely. Several tries are required before achieving a satisfactory outcome. It would honestly be quicker and less expensive to hire a sketch artist on Upwork.

How GenAI is used in Photoshop Generative Fill

Conversely, Adobe offers Photoshop Generative Fill, a GenAI feature. Say, for example, that you would like to swap out the bicycle for a motorcycle by selecting a smaller portion of the image. As a result, the other elements of the image provide stable diffusion with a wealth of context.

In this way, the generated element—”the motorbike” in this case—fits in nicely with the scene. Yes, sometimes it produces subpar results, but compared to the first example, the percentage of high-quality output is substantially higher.

Why did one example perform so well while the other did not?  

When you generate the entire picture without any additional context, it takes a lot of time and usually produces an unsatisfactory result. GenAI is revolutionary when used for smaller context-driven components.

What does that imply for test automation using GenAI?

If you use a GenAI feature to create test cases, the results are unhelpful because the feature is too general. Assume that out of 1000 test cases, 200 of them fail. How are you going to use this knowledge? What benefit does it provide you with? From the standpoint of the user and tester, do these test cases make sense? Are they failing due to the quality of the test case or the subject under test (SUT)?

From a Photoshop Generative Fill standpoint, GenAI will initiate the testing procedures. You tell the system what you want to do step by step. It works similarly to exploratory testing, but you prompt rather than click through the application. The steps are generated by the system once it recognizes the interactions. Within the context of your SUT, the GenAI converts your request into concrete actions.

This trend will also affect future exploratory testing procedures. The system generates automated tests, and you can instruct it what to do. You will then have access to all of the exploratory tests.

AI and autonomous testing are two more buzzwords on the rise in addition to GenAI.And by 2024, they will have greatly increased.

2. You are nothing without AI

To succeed in the market, artificial intelligence is a must. Users and customers are requesting it. Put another way, everyone seeks out tools with cutting-edge artificial intelligence features and wants to be on the cutting edge of technology.

Vendors claiming to have AI and to have it as the newest, greatest thing on the market are becoming more and more common. despite the fact that it only has an external shine. Warning: spoiler alert: it’s not always AI, and, in most cases, it’s not even helpful.

We know. AI is fantastic when applied properly. We actually have a virtual user powered by AI for self-sufficient software testing. Indeed, there seem to be a lot of buzzwords in one sentence. However, it is legitimate, distinct, and the latest sensation on the market as long as it lives up to the hype.

Let’s return to the 2024 AI trend. In order for their tool to have AI, vendors will add AI. It sounds great, looks great, and even offers a hint of utility, but upon closer inspection, it isn’t anything you want to have in your automated testing.

Why? You’re asking yourself now.

Let’s examine a real-world scenario that I encountered last week.

Why a 99% success rate in test automation is insufficient

“With its best-in-class models and 99% success rate in reruns, our artificial intelligence can recognize your software,” someone asserted.

It sounds fantastic, and it’s difficult to avoid falling victim to the 99%. However, what does a 99% success rate really mean?

Assume that your test cases have 100 interactions (a minimal test case; do not confuse test steps with interactions). If your test cases have a 99% chance of passing, this means that only 99 interactions out of 100 will pass, meaning that your test cases will always fail.

That means? A 1% error is 100% flaky.

If you have daily tasks that require more manual labor, the automation won’t be of any use.

A 99% success rate makes automation seem incredibly stable. In 2024, these instances will become more frequent. Remember to challenge those figures and apply appropriate interpretation. Don’t be fooled by the numbers and marketing.

3. Autonomous Software Testing

Autonomous testing is becoming more and more popular. It’s going to be the year’s buzzword, in my opinion.

It will take some more time before complete independence is achievable. However, the first step in this direction will be popularized in 2024 with building blocks that are partially autonomous. This implies that some closed actions, like logging in, will be autonomous. Simply state that you are logging in, and the system will identify whether two-factor authentication is in place and a code needs to be retrieved via email or a mobile device.

Blocks that allow for the definition of requirements and functionality must have closed actions that are easily supervised and devoid of dependencies: The system’s job is to identify every possible way for me to log in, with the end goal of logging in.

The trap of autonomous software testing

Nowadays, when it comes to AI, the term “autonomous” is used frequently, and it usually has nothing to do with testing autonomy. Nobody desires to remain behind. Additionally, since you won’t have a reliable, stable autonomous test solution overnight, vendors will either start adding autonomous features to outdated technology or will suddenly emerge as autonomous vendors.

In 2024, the majority of the new features for autonomous testing will consist of web crawlers that automatically capture screenshots of every link and then scan every link to compare the screenshots with the application. The application behaves differently if it is not the same as the screenshot.

Autonomous testing is not that. The system itself is not used in any way.

When it comes to impressive sales presentations and demos, keep an open mind and be skeptical. Find out if these are just sales gimmicks or if they are genuine autonomous testing.

4. Major Players Get Additional Tools

I’ve got a hunch that 2024 will see a real boom in the little guys getting scooped up. Blame it on the tech from the ’90s holding back the cool, new stuff.

Now, the big shots? They’re going big, expanding their lineup with new tools and services. But here’s the tricky part—blending these newbies with what they already have. It’s like trying to mix different paints without making a muddy mess. And you know what happens? Overlapping offers that leave customers scratching their heads. Imagine trying to decide between two tools that seem like twins—no one likes feeling lost in a tool jungle, right? Which one solves what? It’s a puzzle!

The goal is to cover everything with the available tool stack, rather than focusing primarily on automation. Since they were never intended to be a tool suite, the collection of services and tools is disorganized and cannot be easily combined.

Having a single vendor for the entire tech stack, however, might be appropriate for some, and many businesses might find it unsettling due to overlaps. If your needs aren’t fully satisfied in the end, you might still have to purchase the tools from several suppliers.

5. Greater hype for marketing rather than new ideas

2024 will see an increase in promises and the use of alluring language in place of creativity and cutting-edge technology.

We’re back where we started: differentiating between new, valuable information and hype.

There’s a good chance that something new has been released. However, we observe a trend wherein the more well-known players in the market, who haven’t introduced any novel technological advancements in recent years, typically fall short of their commitments.

These days, you have to hone your inspector skills and determine what is and is not worth evaluating because that is just part of the game.

Wrapping Up

There are tools available that have amazing technology and frequently release new and amazing things. Since there is no label for that, do your research and carefully examine the instruments and promises before committing to anything you’ll later come to regret.

As I mentioned in the introduction, it’s not about pointing fingers. That’s all. The game has changed, and new abilities and questions are required for using and assessing test automation scenarios. One notable change that is still present is the increased emphasis on inspector-like skills for users and decision makers, resulting in less innovation and more buzz. 

Author Bio

Vishnu Narayan is a content writer works at ThinkPalm Technologies. He is a passionate writer, a tech enthusiast, and an avid reader who tries to tour the globe with a heart that longs to see more sunsets than Netflix!

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