Top 5 Software Testing Trends in 2020

According to the World Economic Forum, the value of digital transformation for both society and industry could reach $100 trillion by 2025. Enterprises continue to undergo intense digital transformation and become more dependent on new-edge technologies. This sets high requirements for the stability and reliability of software. Hence, the significance of software quality assurance increases as well.

The share of IT budgets spent on Quality Assurance has improved by 35% since 2015 and is predicted to face another increase by 2020. At the same time, digital transformation presumes experimenting with digital features, which calls for the eligibility and flexibility of the development and QA processes. Therefore, quality assurance faces contradicting demands for flexibility and stability, which sets a challenge for QA managers. They continue to search for non-trivial means of setting QA processes in a way that allows meeting both requirements.

The data storage and development is growing much in number. As per a research at Sogeti, 75-76% of all apps are cloud-based. Eventually companies are gradually moving towards the Internet of Things (IoT).

IoT provides the technology access to the data which was not seen before and the organizations are able to make business decisions accurately as per previous and historical data.

The following kinds of checks will be conducted in the IoT area:

• Scalability testing
• Testing the device with compatibility of versions
• Monitoring and connection delay
• Safety analysis (authenticity of the device, requirement and reliability of authorization)
• Data integrity assessment

Despite the never-ending progressive role of IoT, the World Quality Report released that 34% of the company’s products have Internet of Things functionality and lack testing culture.

All big companies perform testing on all software and its applications to authenticate the software to be error free and strong. Before 2020, performance engineering is naturally replaced by performance testing methods.

It is considerable to concentrate on other factors like customer’s worth, accessibility and realistic usage and arrangement of quality.

Machine learning (ML) is the next exponential technical trend, and it is knocking from the front towards automated testing. It has already led to a revolution in the development sector and the use of applications.

Certainly, the market for machine learning is projected to grow from $1.41 billion to $8.81 billion by 2022, which means there will be more testing solutions for recurring tasks performed by artificial intelligence.

Major tasks performed by the adoption of machine learning:

• Optimizing the test suite: Unique code checks
• Forecast: Prediction of the main test configurations
• Log Analytics: Identification of checks that can (or could) be executed automatically
• Defect analytics: Discovering high-risk application points for prioritizing regression tests

The market for artificial intelligence is also growing faster. It is anticipated that by 2025 it will be worth $190.6 billion dollars. This suggests that the IT business is progressively moving to machine learning.

The test of big data has been penetrated because of the strong parameters that many organizations are following to gel with the latest market trend. As per the prediction the requirement for testing big data apps will grow at its peak in 2021.