The Future of Software Testing

Many software testers have opinions about the future of their profession. Here, László Szegedi takes a look at how today's realities could shape tomorrow's possibilities for testers when it comes to new skills and technologies, roles and dynamics, and tools and devices. What could your job look like a decade or more from now?

There is much talk in the software community about the upcoming trends in software testing—and about whether testers will even still be relevant or necessary in the years to come. I, for one, don’t think automation could replace the exploratory skills of a human tester, but that doesn’t mean our jobs won’t be changing at all.

There are lots of exciting possibilities and opportunities for tomorrow’s testers. Let’s see how this profession can be expected to evolve in the upcoming decade and beyond.

Skills and Technologies

Thanks to user behavior-analyzing tools such as Adobe Analytics and Google Analytics, requirements design can be tailored to specific customer groups. This has great potential to influence the Pareto principle—that 80 percent of your effects (sales, revenue, etc.) come from 20 percent of your causes (products, employees, etc).

Having this data lets you create very specific sets of requirements, specialized to customer profile groups based on their behavior and usage and weighted with expected results from these groups. The fulfillment of these requirements will have to be tested more precisely, so there will be less space for exploratory testing and more reliance on testers using their common knowledge and data analytical skills.

This is what persona testing is based on. This area has just started to develop in the last couple of years. In a few years, I predict we will be pairing persona testing with smart data, or the processed and cleaned big data, to get persona testing frameworks with perfectly optimized and measured A/B testing prototypes. There will be hardly any product, be it a webpage or wearable, without a marketing strategy aiming for the prime focus group, so a targeted approach to testing will hold essential business value. 

I also predict that there will be a greater demand for testers to learn at least some basic programming. Scripting languages are becoming more and more effective and easier to learn; you don’t need to write fifty lines of assembly code to be able to script a test of a login function. Even manual testers are learning languages like Python, Selenium, or Perl because their rich online documentation makes the scripting of routine tasks even easier.

Automation tools also provide fantastic compatibility with functional, object-oriented, keyword-driven, and other kind of programming languages. Their rise makes building precise, fine-tuned automated test frameworks simpler. Consider how useful automation is when performing health checks of production environments in order to help lower the downtime of customer-facing services to a minimum. This is especially important with the rise of ever-available mobile apps and 24/7 services, such as online banking and health care providers.

Roles and Dynamics

Testers and developers are working more closely, with some testers even being embedded in the development or project team. While learning the fundamentals of testing is relatively easy—you often can start working after taking a good course or reading a detailed book—setting up and managing a test process requires years of experience and knowledge, and I don’t see that going away.

This knowledge will also be required in cross-functional teams working with continuous development. While all team members can test a given area pretty well, there’s a definite need for guidance. This also applies to crowd testing mobile devices or cloud setups. Testers may be integrated in other teams, and developers may be asked to perform some testing earlier in the development cycle—and that’s a good thing—but we will still need testers with defined expertise.

User Comments

Bruce Wen's picture

This is the first time for me to know the concept "Crowdsourcing". Thanks!


Currently, I worked as automation test engineer. I have a confusion that what shall automation test engineer do in the beginning phase of big product development. The problem is that the testing process is slow, product feature is not stable. Most of time, automation test engineer has no enough work to do because the automation framework is already muture and what they are wating for is just the requirement from test team. What shall they do?

July 3, 2017 - 1:40pm
László Szegedi's picture

The delayed phase of activity you described is very common among software testers. With good preparing, you can use this time properly. I call this period of software testers "the golden time." It is a perfect for:

  • requirement analysis
  • testing the already developed modules with a hub or a driver - you won't have the time reqiured for such a thorough testing when the integrated system will be ready to test
  • spend the time for your own development, studying the latest trends and technologies you can use later - there won't be time for this later on, neither


July 12, 2017 - 5:56am
Doron Bar's picture

Thanks for the interesting article. I have a few questions.

You say "there will be less space for exploratory testing and more reliance on testers using their common knowledge and data analytical skills."

As far as I know, common knowledge being used is ET.

Using testers "data analytical skills" - is it possible for new features? How exactly? -There is no analytics for features not yet released. What about cases that sometimes you only need one person that will be harmed by a bug in your program to lose your credibility. And you will not see this one person actions in your analytics.

"I also predict that there will be a greater demand for testers to learn at least some basic programming." - True. It is here and called Agile, CI etc.

"developers may be asked to perform some testing earlier in the development cycle" is TDD.

July 6, 2017 - 3:32pm
László Szegedi's picture

Thanks for the well-founded questions!

Data analytical skills might be useful in case of determining the testing coverage and depths of functions where A/B testing and focus groups are defined. But testing medical software of nuclear plant driver, you have to be carefully testing every case, by well-defined and precise requirements, to avoid any harm of a single user, just like you described.

While test driven development is implemented on different levels, other types tests may be required to achieve high coverage. And agile and continuous improvement is not applied everywhere with the same effectiveness -- some companies still use the same manual methods described in the books from the '70,s '80s.

Still, I have to contradict in exploratory testing. My concept is more close to Lee Copeland's definition: simultaneously plannig, exectuing and assessing tests, leaning the sbehavior of the system. Techniques as reversing the order of test cases of chenging the user flow might acieve better test coverage thane using common knowledge only.

July 12, 2017 - 6:33am
Minh Nguyen's picture

Thanks for sharing this article.

As far as I know, AI is an emerging technology in the world. So how would a test engineer be in the next 10 years if it can write code by itself without the training from a bunch of datasets?

July 7, 2017 - 5:32am
László Szegedi's picture

AIs are really developing and already in use on many areas. Still, scheduling and managing them remains a human job for a long time. The era of Skynet from the Terminator movie is still not here, fortunately. But the time is definitely coming.

July 12, 2017 - 5:59am

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