1. Artificial Intelligence and Machine Learning (AI/ML) in Testing
Applications of Artificial Intelligence/Machine Learning for several years have been leveraged in software automation testing. AI/ML help software testing teams to optimize their test automation strategies, speed up the adaptation process and operations.
2. Test Automation in Agile teams
2019 has witnessed over 44% of IT organizations automate 50% or more of testing.
With this rate adoption of automated testing will climb to a new level this year.
As more organizations adopt DevOps and agile practices to fulfill one common need -Quality at Speed of software development, test automation has become a vital component.
From supporting teams in performing repetitive tasks, faster and more accurate detection of bugs to providing continuous feedback test automation comes a lot in play. As a result, organizations save money, human resources and time when they integrate automated testing in QA processes.
3. Big Data
In a variety of business verticals, from technology, banking, healthcare, retail and more, Big data plays an essential role. The focus on optimizing the decision-making process by employing data has greatly risen, this is major because, with the help of big data, industries can deal with diverse data types as well as large volume of data.
Therefore, big data is expected to grow as many industries are shifting their focus towards a data-oriented world.
4. QA Sees Changes in DevOps Transformation
If you’re not familiar with the term “QAOps”, this would be a good time to understand it.
DevOps a rather more familiar term is the combination of development (Dev) and information technology operations (Ops). DevOps practices aim to shorten (SDLC) system development life cycle and teams can focus on developing features and fixing bugs.
The role of QAOps is to improve communication flow between testing engineers and developers.
QAOps can be defined in two fundamental principles:
· QA engineers are involved throughout the CI/CD process and work in alignment with developers
· QA activities are incorporated into the CI/CD pipeline
5. IoT Testing
The number of IoT devices is expected to reach 20.5 billion in the year 2020.
These IoT devices must undergo rigorous for trustworthiness, ease of use, security assurance, scalability, data integrity evaluation, device authenticity, compatibility and more.
Testing engineers have to deal with a lot of work, predominantly in monitoring communication protocols and operating systems. Accordingly, QA teams need to broaden their skills in security, testing, and performance of IoT testing.
6. Demand for Cybersecurity
Digitalization has been great but continuous evolution comes with security threats.
Making the products resilient to threats and taking cybersecurity to the next level is of high priority for CIOs and CTOs from almost every sector.
Security testing helps secure the end-user, data and transactions. Cyber-attacks can take place in any form, testing for security will be a priority for many businesses.
