Top 5 Emerging Software Testing Trends to Watch in 2019

Published in

Blaze Threads

5 min readAug 8, 2019

The software testing methodologies have greatly evolved in the last decade. Software testing has a multitude of functional and non-functional testing methods to deliver optimum results. The rapid changes in the software development and testing sectors demand not only the developers but also the testers to strive to upgrade their skills continuously.

The top software testing firms are well-versed in the different testing modules such as acceptance testing, regression testing, reliability testing, security testing, and many others. In the age of technology, businesses are most vigilant about the performance and security of their software. To ensure their clientele receive unmatched services, the testing companies are adapting new and upcoming trends into practice.

So let’s check out the top 5 trends that will transform the testing industry in 2019:

1. IoT Testing

Internet of Things is a rapidly growing technology, and this has led more customers to opt for IoT testing for their product. Software testing is essential to ensure the functionality, security, and effectiveness. IoT testing process mainly implements five types of testing:

Usability Testing: It verifies the UX quality offered by an IoT device.
Compatibility Testing: As the name suggests, this method tests the compatibility of IoT systems and devices used within the system.
Performance Testing: This method checks the simultaneous communication between multiple IoT devices and servers.
Reliability and Scalability Testing: Virtualization tools are used to stimulate sensors, verifying the reliability of the software.
Security Testing: This is the most important testing module. This validates the authentication process of users and data privacy controls.

2. Machine Learning in Testing:

Machine learning has significantly changed the testing process. The goal is to write new test cases dynamically by data-mining based on user interactions. Moreover, the machine assists quick recovery of tests. Machine learning can also be utilized to:

Optimize Test Suite: This is performed to distinguish between repetitive and unique test cases, thereby using the most optimal testing process.
Predictive Analytics: It is important to analyze the historical data to identify critical parameters of software testing.
Traceability: Requirements Traceability Matrix (RTM) contains keywords in abundance. To ensure sufficient coverage of test cases, machine language extracts keywords from RTM.
Defect Analytics: Machine language plays a critical role in pointing out applications with high-risk.
Log Analytics: Certain test cases have to be executed manually instead of automatically. Machine language assists in identifying such unique cases.

3. Digital Transformation

Businesses require a digital transformation in the era of technology. Moreover, data has gained a prominent position in enhancing business insight.

To match the pace, most companies are adopting an agile methodology to speed up digital transformation. The agile approach uses an incremental method to deliver new and enhanced features with each sprint. This testing module considers smaller portions of the software for testing and delivers quick and accurate solutions.

Within this system, there is also a continuous communication between the developers and the testers, allowing the best software developers to deploy the software on time and without errors. The modernization of the agile testing also boosts the User Experience (UX) with the assistance of proper planning, execution, and evaluation of the software.

4. Service Test Automation:

Service test automation is simply creating software that is specifically developed to test for certain predetermined conditions. Parts of software are created and tested to connect them later without any hitch. Moreover, API and services are used multiple times across different applications and components. Thus, it is requisite of the testers to test the API and services independently, apart from the applications used by them. This makes testing more effective and efficient.

The trend of service test automation has outpaced end-user testing modules as a whole. This methodology also gives the developers a chance to make changes on a smaller, more specific segments as suggested by the testers rather than rewriting/recording an entire software. But most importantly, this optimizes the time taken to deliver the software and thus, encouraging more clients to do business with the company.

5. Big Data Testing

As stated earlier, data plays a crucial part in the growth of a business. But most businesses fail to manage and optimally use the large volume of data acquired by their team of researchers. In the case of software, unorganized or clustered data can lead to the failure of the software. Big data testing allows testers to analyze where terabytes of data within the software are successfully and efficiently processed or not. This type of testing focuses mainly on the processing performance and functionality of the vast data.

To perform flawless big data testing, the testers require overtly analytical tools, unmatched techniques, and optimum frameworks. Moreover, big data testing has to also offer a scope of expansion in the dataset. Specified load testing and stress testing has to be combined with big data testing to ensure that the software can handle an augmentation in the data and also determine the data limit of the software.

Conclusion

There are certain trends in software testing that are evergreen, whereas certain trends lose their value over time. Companies and software testers need to stay aware of the latest happenings of the industry and upgrade their strategies from time to time. However, certain testing methodologies also depend on the type and purpose of the software. To stay ahead of the curve, it is critical to have a thorough knowledge of the new and emerging trends as well as study existing testing systems.

The main goal of software testing is to verify that the software is error-free, and offers a frictionless experience to the user.

But a time-taking software testing process can delay the deployment and certainly lose clients. Therefore it is of utmost importance that companies choose a reliable and efficient testing service provider. You can check out GoodFirms.co to study various testing companies categorized based on testing modules employed, countries, states, and even cities and find the most suited partner for your project.

Enjoyed This Reading?

Give us some claps and share the knowledge with your friends and network.

To stay updated on Digital Transformations and Innovations across various sectors in our environment,