The Future of Software Testing


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.

Tools and Devices

With so many connected options today, customers need to be able to use websites on all kinds of devices. Mobile testing is already becoming so widespread that it is not a separate artifact anymore. The variety of mobile devices will only increase over the years, so the scope of testing will be huge.

Here come the handy crowdsourced testing services. This option lets you make sure your native or web apps work properly under all kinds of conditions all over the world. In coming years, the testers responsible for managing crowd testing will have to drive frameworks testing these use cases, so this would be a useful area to learn more about now. 

Another option for parallel testing on many environments is the cloud. The biggest challenge right now is the configuration of the test systems, but companies facing this challenge will surely provide some compact solutions in the near future—and they will be more efficient and inexpensive. Already, there’s no comparison between the cost of cloud testing and the cost of testing real, physical devices used even five years ago. This cost will continue to get lower and lower, just like shipping costs with containers over the last decade. 

In contrast, a new technology that seems to be developing relatively slowly is self-driving cars. It will probably take years for governments around the world to create appropriate laws for having these vehicles on the road, but meanwhile, companies will keep creating a variety of self-driving cars (just like Google is doing right now), and all of them will have to be tested for all important use cases.

Just as when it’s a person behind the wheel, there are many factors to consider, so a complicated risk-based test approach will be needed for testing activities. Although there are still gray areas of these use cases, some companies started the groundwork for this type of analytical testing by using test cars with cameras and recording devices. As the number of companies producing self-driven cars rises, this testing need will also go higher, and due to the safety-critical nature, it won’t be available for freelancers—this scope will definitely be confidential and will require expert testers.

And there’s another burgeoning field that sci-fi writers have been dreaming about for a while: the everyday use of robots. This has already started to be a reality in Japan, and the technology is at different levels of development all over the world. The producers already perform a huge testing activity before putting these robots into use, but a new dimension will open when the robots can connect to social media and the internet of things. These connections will bring up dozens of integrity and security questions. I think the most effective way to test them will be through crowdsourcing, just like we do now with mobile testing.

There is a lot to learn to keep up with software testing in the next couple of decades. What will you start with?

User Comments

George Boitor's picture

Thanks for sharing your opinion with the community.

Below is my opinion on this subject and on your article:

I choose to see testing (by testing I mean Quality Assurance) based on the context and the risks that might appear.

You raised some interesting points here that in some contexts would apply properly, but in others not so much. From my experience the points you raised apply best to FE Testers of Web Applications(UI) not so much on the Back End part (DBs, Environment, APIs, other Back End Applications, ...). Analitics can help a lot and can drive many testing approaches but I cannot see them as a Driving Force/Approach for all the software testing.

Regarding Skills and Technologies, I see them as the driving force of future QAs; the Waterfall Tester era is almost gone, replaced by the DevOps QA - Tech and Bussiness Specialist that knows how to 'Test' an application based on the context(what, how and why) and risks. Most of the tools and devices can be found/used as a SaaS or/and we can create the 'Test Environment' in the cloud (it's not that challenging if you take it one step at a time).

September 29, 2017 - 10:02am
carlo marchi's picture

Hello, one doubt about Pareto Rule: from my prospective this approach can result either in exploratory testing or in analytical testing because it depend on the causes (20%) that generate 80% of effects.

Using a practical example: small area of modules (20%) could tend to contain most defects of software (80%). This could be achieved by using exploratory testing or error guessing techniques.

What do you think?

January 16, 2018 - 7:18am
László Szegedi's picture

My idea is to approach that 20% of modules with thorough test planning and leaving enough time for exploratory testing. So both techniques are viable, and I even love exploratory better. Do you also?

January 16, 2018 - 7:30am
carlo marchi's picture

Agree. Exploratory testing can be a useful technique when ther are few/inadequate test basis and sever time pressure or no knowledge on application/system to be tested, so tester experience with structured approach is used to explore software, learn from it by testing and find unexpected outcomes. My goal is to focus the "exploration" on basic functions or happy-path

January 18, 2018 - 11:09am


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