10 software testing trends that are worth paying attention to in 2019
- Transfer
Hello!
On the eve of the launch of the course “QA-specialist” , which starts in 10 days, we want to share material that will tell about new approaches in testing and will be useful to everyone who follows new trends and remains in good shape.
With the advent of technology Agile and DevOps, the software industry is undergoing major disruptions. This has led to the development of new approaches to testing. Quality assurance professionals must quickly adapt to changes in the software testing industry in order to remain relevant. Here is a list of 10 software testing trends to look out for in 2019:
1. Digital Transformation with Agile
Enterprises are undergoing digital transformation since the data became valuable. The latest addition to this trend is the adoption of agile for digital transformation. Agile Methodology helps align digital transformation initiatives with business needs.
Agile team defines business objectives, goals and use cases. In a flexible way, new features are provided gradually with each sprint. Because digital transformation is an ongoing process, a flexible system helps deliver valuable business results more often without a long wait.
2. Machine learning in testing
Machine learning leads to revolutionary changes in workflows. In testing, machine learning can be used to:
Optimize test cases — to identify redundant and unique test cases.
Forecast analytics - to predict the basic parameters of software testing processes based on historical data.
Log analysts - to determine test cases that need to be performed automatically.
Traceability - extract keywords from the requirements tracking matrix (RTM) to provide test coverage.
Defect analysts- identifying high-risk applications for prioritizing regression tests.
3. Increased acceptance of DevOps
In DevOps, testing begins at the beginning of the development cycle. This design approach facilitates continuous integration and continuous delivery. This allows testers to perform continuous testing and continuous monitoring to confirm that developers have created the right application. The functionality and performance of the application is constantly being tested along with the development.
The testing team integrates test design, test automation and test case development with DevOps to not only verify code changes, but also ensure that these changes do not damage the product.
4. Testing Big Data
Big Data is a large amount of data generated at high speed. When testing big data, testers must ensure that terabytes of data are successfully processed using the product cluster and other supporting components. This type of testing is focused on performance testing and functional testing.
Data quality is also a critical factor when testing big data. Data quality is checked prior to testing. It is tested on the basis of various characteristics, such as conformance, accuracy, consistency, reliability, duplication, data completeness, etc.
5. IoT testing
There are more connected devices than ever before, as the Internet of Things (IoT) technology is gaining momentum. IoT testing is conducted to test devices based on IoT technology. Different types of testing for IoT systems:
Usability testing - for testing the usability of the IoT system
Compatibility testing - checking the compatibility of devices in the IoT system
Testing the reliability and scalability - simulating sensors using virtualization tools
Testing data integrity - for checking data integrity
Testing security - for testing the process user authentication and data privacy control
Performance Testing — To test the performance of connected devices on an IoT
6 network . Performance Performance
engineering will replace performance testing in 2019. Instead of running performance test scripts, the focus will be on analyzing how all elements of the system work together. The various elements of the system include performance, security, usability, hardware, software, configuration, business value and customer value. Performance engineering is the collaboration and iteration of the most valuable products, as well as the rapid delivery of these products to ensure high quality products. Performance engineering will help transcend user queries in 2019.
7. Testing Automation Testing
automation helps the testing team focus its time and effort on creating test cases , rather than managing test needs. Test automation helps track and manage all testing needs, types of testing required, and test coverage. Test automation helps ensure the delivery of high-quality software.
Specialized tools are used to monitor the performance of tests to compare actual results with expected ones. Mostly regression tests that require repetitive actions are automated. Automation tools are used for both functional and non-functional testing.
8. Combining manual and automated testing.
More and more quality assurance professionals are using a combination of manual and automated testing approaches to take advantage of both and overcome their disadvantages. Manual testing still dominates the testing industry. Although automated testing ensures the effectiveness of the testing process, there are still certain areas, such as usability and design, that require manual effort.
9. Reduced delivery cycle
Rapid changes in technology, platforms and devices make software development teams faster and more often deliver finished products. Testing should be integrated with the development to facilitate delivery. Software development organizations are ready to invest more in improving their development and delivery processes using the right toolbox. The need for testing management tools will increase to meet shorter delivery cycles.
10. Integration
With shorter delivery cycles, there is a great need to integrate the various elements of product development. To simplify intelligent testing and analytics, data is collected from diverse sources, such as requirements management systems, change management systems, task management systems, and test environments. This implies the need for integrated tools that help with requirements management, task management, error tracking and test management. The integrated tool acts as a data repository of various modules that can be used and shared.
Conclusion
To keep abreast of events, quality control professionals need to be aware of the latest testing trends. The only way to be immune to disruptions in the software industry is to prepare for the future. The above software trends will help testers invest their time and effort in acquiring the right skills and tools for 2019.
As always, we are waiting for your comments and invite you to an open webinar , which will be conducted by a certified tester Nina Devayeva .
On the eve of the launch of the course “QA-specialist” , which starts in 10 days, we want to share material that will tell about new approaches in testing and will be useful to everyone who follows new trends and remains in good shape.
With the advent of technology Agile and DevOps, the software industry is undergoing major disruptions. This has led to the development of new approaches to testing. Quality assurance professionals must quickly adapt to changes in the software testing industry in order to remain relevant. Here is a list of 10 software testing trends to look out for in 2019:
1. Digital Transformation with Agile
Enterprises are undergoing digital transformation since the data became valuable. The latest addition to this trend is the adoption of agile for digital transformation. Agile Methodology helps align digital transformation initiatives with business needs.
Agile team defines business objectives, goals and use cases. In a flexible way, new features are provided gradually with each sprint. Because digital transformation is an ongoing process, a flexible system helps deliver valuable business results more often without a long wait.
2. Machine learning in testing
Machine learning leads to revolutionary changes in workflows. In testing, machine learning can be used to:
Optimize test cases — to identify redundant and unique test cases.
Forecast analytics - to predict the basic parameters of software testing processes based on historical data.
Log analysts - to determine test cases that need to be performed automatically.
Traceability - extract keywords from the requirements tracking matrix (RTM) to provide test coverage.
Defect analysts- identifying high-risk applications for prioritizing regression tests.
3. Increased acceptance of DevOps
In DevOps, testing begins at the beginning of the development cycle. This design approach facilitates continuous integration and continuous delivery. This allows testers to perform continuous testing and continuous monitoring to confirm that developers have created the right application. The functionality and performance of the application is constantly being tested along with the development.
The testing team integrates test design, test automation and test case development with DevOps to not only verify code changes, but also ensure that these changes do not damage the product.
4. Testing Big Data
Big Data is a large amount of data generated at high speed. When testing big data, testers must ensure that terabytes of data are successfully processed using the product cluster and other supporting components. This type of testing is focused on performance testing and functional testing.
Data quality is also a critical factor when testing big data. Data quality is checked prior to testing. It is tested on the basis of various characteristics, such as conformance, accuracy, consistency, reliability, duplication, data completeness, etc.
5. IoT testing
There are more connected devices than ever before, as the Internet of Things (IoT) technology is gaining momentum. IoT testing is conducted to test devices based on IoT technology. Different types of testing for IoT systems:
Usability testing - for testing the usability of the IoT system
Compatibility testing - checking the compatibility of devices in the IoT system
Testing the reliability and scalability - simulating sensors using virtualization tools
Testing data integrity - for checking data integrity
Testing security - for testing the process user authentication and data privacy control
Performance Testing — To test the performance of connected devices on an IoT
6 network . Performance Performance
engineering will replace performance testing in 2019. Instead of running performance test scripts, the focus will be on analyzing how all elements of the system work together. The various elements of the system include performance, security, usability, hardware, software, configuration, business value and customer value. Performance engineering is the collaboration and iteration of the most valuable products, as well as the rapid delivery of these products to ensure high quality products. Performance engineering will help transcend user queries in 2019.
7. Testing Automation Testing
automation helps the testing team focus its time and effort on creating test cases , rather than managing test needs. Test automation helps track and manage all testing needs, types of testing required, and test coverage. Test automation helps ensure the delivery of high-quality software.
Specialized tools are used to monitor the performance of tests to compare actual results with expected ones. Mostly regression tests that require repetitive actions are automated. Automation tools are used for both functional and non-functional testing.
8. Combining manual and automated testing.
More and more quality assurance professionals are using a combination of manual and automated testing approaches to take advantage of both and overcome their disadvantages. Manual testing still dominates the testing industry. Although automated testing ensures the effectiveness of the testing process, there are still certain areas, such as usability and design, that require manual effort.
9. Reduced delivery cycle
Rapid changes in technology, platforms and devices make software development teams faster and more often deliver finished products. Testing should be integrated with the development to facilitate delivery. Software development organizations are ready to invest more in improving their development and delivery processes using the right toolbox. The need for testing management tools will increase to meet shorter delivery cycles.
10. Integration
With shorter delivery cycles, there is a great need to integrate the various elements of product development. To simplify intelligent testing and analytics, data is collected from diverse sources, such as requirements management systems, change management systems, task management systems, and test environments. This implies the need for integrated tools that help with requirements management, task management, error tracking and test management. The integrated tool acts as a data repository of various modules that can be used and shared.
Conclusion
To keep abreast of events, quality control professionals need to be aware of the latest testing trends. The only way to be immune to disruptions in the software industry is to prepare for the future. The above software trends will help testers invest their time and effort in acquiring the right skills and tools for 2019.
As always, we are waiting for your comments and invite you to an open webinar , which will be conducted by a certified tester Nina Devayeva .