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1.1       Introduction

Quality Assurance Teams should keep ahead from Development Trends if they want to become as pro-active and efficient as possible. With the ever changing landscape of Development with new methodologies and tactics, the software development industry is becoming fluctuated and more distorted by the minute.

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If Software Testing wants to stay relevant throughout all of this it is vital that certain trends and alternative methods are not to be taken lightly.

1.2       Agile Development And Its Transformative Nature

Agile Methodologies are taking the high ground lately especially when it comes to aligning digital initiatives inside business models to fit their needs. These techniques and strategies basically define most business challenges & use cases in our industry today. Basically what this means is that new features are hitting the product with each mini release while going through all phases of Software Testing. This of course helps in producing a proper outcome for the businesses that need it rather than pledge to wait prolonged periods of time..

1.3       The Use Of Machine Learning

Being of a more innovative nature, Machine Learning is changing the game with better workflows and processes. It can be used for various things, such as Predictive & Log Analytics. This means that parameters inside the software testing process will be, well, predicted as well as which test cases need to be executed automatically and which don’t. Also, redundant and unique test cases are not made equal, Machine Learning helps discern which is which. In order to acquire full test coverage, Machine Learning extract keywords from the RTM or otherwise known as the Requirements Traceability Matrix. Last but not leas comes Defect Analysis. By identifying high risk areas of an individual app we can prioritize regression testing cases immediately.

1.4       The Increasing Adoption Of Trends

Latest methodologies in DevOps make sure that testing begins in the beginning stages of the development cycle. This facilitates the usage of CD, CT & CM in order to make sure that the right application has been built with proper components in place. It is not uncommon for Big Data to take center fold now and then in order to verify even terabytes of data being processed or successfully provided in the commodity clusters and other components. As the IT industry grows, so to does the need for IoT. But as it is, it requires different ways of testing on its own such as reliability checks, compatibility issues, data integrity, security and so on. Each phase represents a valuable piece of a much bigger puzzle. Nowadays the difference between Manual & Automation Testing is visible as more and more professionals are using a hybrid of the two in order to get the best results possible. Where automatic testing brings more efficiency while manual testing brings more quality. All of this shortens the entire delivery life cycle and integrates everything seamlessly in to its target environment.

1.5       Conclusion

Times are changing and so are technologies. As previously stated, Testing has to keep up with the ever changing landscape of Development if in turn proficient results are to be met and delivered to our customers.