Top 5 Testing Trends to Watch Out For

Testing is an important part of the development process, which is why it’s important to follow its evolution. That begs the question: What are the most interesting trends in the foreseeable future?
November 29, 2021
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In this modern, fast-moving world, consumers want fast deliveries and frictionless experiences. The market has never been more competitive and demanding. People want great products developed in record time.

To meet these increasing demands, companies have had to adapt and improve. They have developed new methodologies focused on flexibility, automation has become the norm, and continuous delivery is their main goal.

No development pipeline, no matter how meticulous, can deliver a functional product without a solid software testing strategy. Computer programming is a complicated science in which even the smallest slip can snowball into an avalanche of consequences.

Testing helps make sure that products are up to par with the expectations of consumers and end users. Companies use software tests to check for bugs, to measure performance, to examine corner case scenarios. All with the intent of crafting and delivering a stable and functional product.

There are dozens upon dozens of testing strategies, from unit testing to functional prototypes— companies have a plethora of tools at their disposal. And with the advance in cloud computing, AI, and the Internet of Things,  there are new trends emerging every single day that help create faster and more accurate testing strategies.

Here are 5 of those trends that you should be paying attention to. 

#5 Shift Towards Performance Engineering from Performance Testing

Performance has always been a sore spot for software development. In theory, you could build any kind of software to process any amount of data imaginable. The problem is, do you have the resources to pull it off?

Performance testing is fundamental in every project. Unfortunately, the test is only able to assess performance issues late in the development cycle. As such, there has been a shift towards performance engineering with the adoption of agile methodologies.

With performance engineering, QA teams design the applications from the beginning of the development cycle. Resource requirements are tracked at each stage with performance becoming an important indicator.

The goal is to solve performance issues early in the process. This saves time in the long run since each bottleneck is handled without compromising other areas of the project. It’s also a sound strategy to avoid unnecessary hardware acquisition costs.

#4 QAOps

Software developers are under constant pressure to release their products at a brisk pace. However, constant and faster delivery often comes at the cost of quality. This is a fundamental problem in every engineering project and one that lies at the center of project methodologies.

QAOps is a new approach that takes the speed and automation of DevOps and the extensive practices of QA engineering and meshes them together to provide a faster and seamless process.

QAOps follow 3 core principles:

  • Enhanced collaboration between developers and QA engineers
  • Integrated continuous testing in DevOps with a CI/CD pipeline
  • Integrated, defined, and streamlined QA processes pushed into DevOps while pulling the QA team out of silos

Akin to Performance engineering, QAOps introduces QA throughout the Software Development Life Cycle (SDLC). QA teams are more integrated into the project, and their feedback shapes the development process.  

#3 Automated Testing

There are 2 kinds of testing in the world of software development: Manual testing and automated testing. In the former, humans test the project, either by manually running the test on the code or by interacting with the final product.  

On the other hand, automated testing is a method in which automation tools are used to control the execution of tests. The results are then compared with predicted or expected results. 

In comparison to manual tests, automated testing offers greater efficiency and faster time-to-market. Having said that, some forms of manual testing like discovery testing or usability testing are invaluable and can never be automated. For example, only a human can tell if something feels comfortable to use.

Usually, automated testing requires programming since the tests have to be coded and implemented. But in the last few years, we’ve seen an upsurge in codeless test automation. By using AI and visual modeling, developers can create and deploy faster testing scenarios.

Another trend is Robotic Testing Automation (RTA), which involves automation testing tools that help replace regression and load testing, reducing manual input requirements.

#2 Cyber security testing 

Cyberattacks have been on the rise ever since the pandemic started and companies went remote. It’s the nature of the beast: Whenever we are online we are exposing our work to hackers and cybercriminals. 

Cyber security testing is a series of methodologies and tactics developers apply to search for critical vulnerabilities that can be exploited in their projects. Build reviews, vulnerability assessment, penetration testing, and red team assessment and some of the most common and widely used approaches.

Cyber security can be done in-house, but it’s also quite common to hire a consultant to help with the process. This is one of those cases where an outsider’s point of view is extremely important, as consultants can look at the project objectively and find gaps that might otherwise go unnoticed.

Security testing is never truly done. Technology advances, and with it, new ways to breach security are developed with every passing day. Likewise, as projects grow and change new code might also create new vulnerabilities. 

Routine security tests are always a good idea, especially in an age where you have to be compliant with data protection laws such as the GDPR.

#1 IoT Testing

It should come as no surprise that there is a growing need for IoT testing with the increase in IoT services. Testing for IoT devices revolves around analytics, security, networks, processors, platforms, and standards.

The most common types of IoT Testing are:

Compatibility Testing: Perhaps the most important aspect of IoT testing is to make sure that different devices can actually connect and communicate. There are hundreds of software and hardware configurations, and certain combinations might be problematic or outright impossible.

Usability Testing: Just like software testing, it’s important to assess if a particular device is adequate for the end user. Can you install the device and be ready to go? Is the user going to need training? Does the device satisfy the needs of the user? Those are some of the questions you have to ask yourself. 

Reliability and Scalability Testing: When you are building an IoT environment it’s extremely important to check the reliability of your system. How much stress can it handle? How often does it require maintenance? What is the minimum margin of error? One part of reliability is testing how the system behaves after scaling. 

A change in testing paradigms

Back in the day, testing used to be done when a project was close to completion. A final check-up before delivery. But with agile methodologies growing in popularity it’s no longer viable to leave testing as an afterthought. 

Testing has become an integral part of the software development process. One that helps you deliver the best product possible, especially when you take into account the latest trends, which can provide better results and more robust applications. 

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