In the past few years, we have witnessed tremendous advancements in the software testing industry. The experts introduced a lot of new technologies and many smarter testing procedures which have revolutionized the software testing field. Modern-day testing services providers are putting their efforts to deliver high-quality software solutions more speedily. To achieve this goal, they are adopting new technologies in software testing and constantly working to improve their procedures.
The one major change we have seen is the shifting of software testing procedures from manual methodologies to test automation. Automation has become a big thing nowadays because of its benefits and effective end results.
However, new trends still require more advancements and there is a lot more to come in the software testing field.
This article provides information about the new trends and emerging technologies that are going to be the future of software testing.
Advancements in Test Automation:
Test Automation is giving tremendous benefits already. It provides faster results for regression testing and eliminates the need for performing repetitive tasks. Test automation helps to make possible the timely delivery of the software product. Also, there are a lot of test automation tools that come to the market to help make the test automation technique easier.
However, there are still some testing areas that need manual testing techniques to function properly, for example, usability testing, exploratory testing, UI/UX design testing, etc. Test automation is not applicable to every aspect of testing but more working on the enhancement of the automation itself can trend in the future.
No Code Automation Testing:
Another trend likely to arise in the future of testing is “no code automation testing”. In currently popular automation testing services, testers need greater knowledge of programming because they have to write code for test scripts.
However, in the future, no code automation testing may become more favored because it does not require any detailed knowledge of coding to create test cases.
How does it work?
No code automation is the new technology in software testing that helps testers in creating the logic of the application with no complex coding. It provides an interface to record required test cases. Hence, it allows you to create automated code within a few minutes because you don’t need to write code from the start for every test case.
Why is it becoming a new trend?
No code automation is the future of software testing because of following reasons:
- It is time saving because testers don’t have to waste time on writing long codes to execute test cases.
- It’s easy to understand so your team doesn’t require any comprehensive understanding of the tools and procedures.
- It’s an efficient way to test products because you don’t have to start from scratch.
- Helps non-technical team members to perform their work smoothly.
Robotic Process Automation (RPA):
RPA is likely to take over the future of software testing. It is a process automation technology that enables a system to perform duties of humans and optimize the efficiency of work. As robots are being used for lots of other functions, we can say that the robots will help humans in software testing procedures as well.
Experts consider RPA to take over the testing field just as test automation took over it in the past few years.
How does RPA Relate to Software testing?
RPA, when used for software testing, helps to automate the software testing flow with minimal human intervention. If a user performs some action in GUI, the RPA system is intelligent enough to repeat it as per the instructions. This is the feature that is making this technology famous in the software testing industry.
There are several RPA tools being used in automation techniques, such as big data tools that help to deal with huge amounts of data. In the future, as the needs of the industry will strengthen, RPA will also become more refined.
AI/ML for Software Test Automation:
Using Artificial Intelligence (AI) and Machine Learning (ML) is likely to be a new future trend. Although this concept is already helping in the software testing field. However, this concept requires more advancements and applications in this field.
There are several tools used for software testing which are based on AI concepts. However, in the future, these tools can give their suggestions to make the automation code scripts flawless.
How AI/ML can be Beneficial in Future?
Software testing services will become more powerful if experts use AI/ML concepts in software testing as it yields following benefits:
Identifying Bugs More Efficiently:
ML in software testing is helpful to identify even those issues which may remain unnoticed by testers because of any reason.
Test Process Optimization:
AI and ML can help to determine the most efficient test cases for issue recognition based on their information.
Help in Regression Testing:
With the help of AI, testers can monitor changes in the code and review overall test coverage, which helps in effective regression testing.
Big Data Testing:
Big Data refers to a large amount of data that companies use for various business purposes. As the use of big data is increasing in modern businesses, the big data testing services also need to be defined.
Big Data Testing Procedure:
Here are some aspects that need to be covered while performing big data testing:
Check Data Integrity:
Big data integrity helps to identify any duplications or problems with data completion.
Test Data Validation:
Data validation determines whether the big data is accurate and as per the business demands.
Check Data Ingestion:
This operation makes it sure that the big data is stable and easily available on demand.
Perform Data processing:
This step enables users to check the results of performing business logics on data and behavior of data in return.
Data Storage and availability:
In this step, testers check the performance and availability of data in response to specific queries.
Reporting:
It deals with the reports that show the overall status of the data.
Conclusion:
As the new trends affect customer requirements, and customers try to demand the functionalities according to the state-of-the-art trends, Codeautomation.ai professionals stay informed in this rapidly changing era so that we can provide our services as per user requirements.
