5 Things That Will Impact the Future of Software Testing

In the past decades, software testing has evolved the terms of both the tools used to perform the different activities and the mindset of people using those tools. There used to be only a handful of tools used in software testing, but now we have a plethora of tools to choose from proprietary to open the source. Likewise, people have started to think of testers as information brokers instead of gatekeepers, and there have been a lot of positive developments in the agile world that have contributed to significant changes in the process that teams follow in their software development lifecycle.

Advancements in technology are to thank for these evolutions.

5 Key Things to Shape the Future of Software Testing

  1. Artificial Intelligence:

Five years ago, everyone was talking about “mobile-first” and giving the user a mobile experience using mobile web, native, and hybrid applications. Now, the new buzzword is AI. It is self-driving cars, home assistants, computer vision, health care, finance, and now in software testing.

Currently, few reliable tools in the market can use machine learning to help in the authoring and execution of functional testing, end-to-end testing, and regression testing. They are primarily concentrated in UI-based test automation—the more tests the user creates, the smarter the algorithm becomes, which makes the tests more stable.

Here are some of the benefits we could expect to start seeing in testing thanks to AI:
  • Easier authoring of tests
  • Lower maintenance work on test scripts
  • Fewer flaky tests
  • Having nontechnical people start doing automation
  • Easier CI/CD integration
  • More reusable tests

Artificial intelligence is the most talked about technology today, from smart assistants to finance, healthcare, agriculture, military, and even software testing. However, the market still has just a handful of tools based on machine learning to perform end-to-end testing, functional testing, and regression testing.

  1. DevOps:

DevOps has helped software development teams and operation teams to collaborate better, thereby ensuring there are constant automation and monitoring through the software development lifecycle (SDLC), which includes infrastructure management as well.

How is this going to influence software testing? Answer: Everything we do as part of testing is going to change. The changes I foresee include:
  • A need to start automation right at the beginning of the SDLC and ensure nearly all test cases are automated
  • All the QA tasks would need to be aligned to ensure a smooth CI/CD cycle
  • A high level of collaboration would be required to ensure there is continuous monitoring in the production environment
  • All the QA environments would need to be standard
  • The testing mindset changes from “completed testing on this module” to “What are the business risks that have been mitigated in the release candidate?”

Improved collaboration, coupled with more automation, will make the teamwork as a single unit and decrease the SDLC (software development lifecycle), thus helping in faster market release of products.

  1. QA as a Service

Just like how we have SaaS (software as a service), IaaS (infrastructure as a service) and PaaS (platform as a service), we now have QAaaS. Over the past few years, this has become a popular way for companies to meet their software testing needs.

Companies that have QAaaS solution makes different aspects of your software testing process easier by providing:
  • Test case management and maintenance solutions
  • Test automation tools with less need for coding
  • Robust test reporting features with logs, video recording, and screenshots
  • Easy integration with CI systems

Software Testing Company these days uses QA (Quality Assurance) as a Service to meet their software testing requirements. QAaaS providers are likely to implement steps to improve their offerings to beat the competitions, which will have benefits for software testers as well.

  1. The Internet of Things

With the advent of wearables, smart homes, connected cars, and other cloud-based technologies, the internet of things (IoT) have become a big topic of discussion. The fantastic thing about these devices is that there are so many communications and integrations taking place every second.

On a high level, the different communications taking place with a wearable fitness tracker. The mobile app and fitness tracker need to communicate with each other. The data captured by your mobile app should seamlessly integrate with the desktop, mobile web, and tablet versions of the app. All these communications across devices should happen in real-time. All the data travels to and from the cloud, the devices, and the apps.

The application had to limit but useful functionalities. Examples include the ability to view notifications and rewards information, reservations, and locations of hotels, flights, and car rentals. While testing this application, I noticed that when the Apple Watch app was connected to the same app on my phone, there were weird issues. When I minimized the app on the phone, the Apple Watch went blank, showing only a black screen; but when I opened the app on the phone again, the black screen disappeared, and the Apple Watch app behaved normally.

Based on different events triggered, the proper notifications need to be sent to the right user at the right time. All these communications happen over the internet.

  1. Robots

Advancement in technology has already started influencing the way we are doing software testing. It has also caused companies to rethink their organizational structure. The QA team is moving toward being embedded within the development team, and the whole team will own quality. It also will become necessary for the research and development group to be in frequent interaction with the development group. This is in order to make products smarter and more useful for its customers.

There will also be a need to have procedures in place to handle large amounts of data. As well as appropriate computing power to comb through this data to get useful information and feedback. Finally, to make all this a reality, companies need to adopt lean processes. They should also be much more transparent to prevent being an obstacle for innovation. The lean transformation will be vital for effective growth.

Human minds monitor robots who do testing. Robots may be involved in various testing functions, though how far they’ll succeed remain to be seen in the future.
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