Key Trends in Software Quality Assurance (QA) To Look Out For
”Quality is the result of an intelligent effort, not a chance happening” – Nassim Nicholas Taleb
Quality Assurance is a methodical and fastidious process of determining whether a product or service meets the specified requirements. Instead of being referred to as an “act”, it is rather a “process” that is strategically conducted throughout the different stages of a specific project.
Since QA is not a one-time operation, it becomes obligatory for businesses and companies to upgrade their QA process as per the lingering trends. Moreover, the dynamic nature of the software development industry brings additional challenges and opportunities for corporations to explore emerging trends in QA.
In the following article, we shall traverse some of the salient trends in QA and how your company can keep up with them for successful outcomes.
QA Automation / Automation Testing
Developing automation scripts to run tests on the software by leveraging the automation tools is what is known as QA automation. The automation scripts used can be executed repeatedly to perform repetitive testing tasks.
Automation testing uses frameworks and tools to trigger tests and run them at scale instead of manual automation.
Venture Beat compared the two and derived that manual testing demands 3-5 days, while QA automation can be completed within 3-6 hours.
Once the right testing environment is set with maximised coverage across multiple scenarios, the test team schedules and tracks the environment setup activities, installing the necessary hardware and software, and developing test bed scripts.
The scripts written by QA engineers are used to perform the tests- be it GUI (Graphical User Interface) or API (Application Programming Interface) testing. Following the execution of the tests, the automated QA tool generates a report that carries information about other possible bugs and defects, paving the way for further testing.
Why Should Your Company Adopt QA Automation?
Drop in the execution time and overall costing
Less room for human errors
Improved test coverage
Reusability of test scripts
Faster development and delivery
Adoption of DevOps
In order to shorten the systems development life cycle, DevOps is a practice that is adopted in the Systems industry which automates the work of software development with the help of various tools and technologies.
The convergence of QA and DevOps befalls at the strategizing phase itself. The developers undertake unit tests on their code while the QAs actively indulge in fixing the code, as and when required.
With the inculcation of DevOps, developers and QA remain on the same page across all the project stages. The absence of DevOps can result in the high possibility of system cash on the release of the code.
Why Should Your Company Adopt DevOps?
Faster and frequent delivery of software products/services
Better reliability throughout the development and testing process
Better engagement between the software team and users
Integration of IoT Testing
The year 2022 witnessed 13.14 billion IoT-connected devices, and the same is expected to upscale and reach a staggering number of 29.42 billion appliances and gadgets by 2030. This vindicates the revolutionary technology, that is IoT.
IoT-based testing entails QA test execution to verify the functionality, UX, network connectivity, performance, and security of IoT devices. It helps build a well-connected and structured smart device that holds the capacity to eradicate any vulnerabilities or threats.
Such a comprehensive accompaniment to QA testing ensures that IoT devices transmit sensitive information wirelessly and seamlessly. This is why IoT companies rely on IoT QA testing for detecting defects before reaching the end users and delivering the desired results.
Why Should Your Company Adopt IoT Testing?
Seamless integration and interoperability across different IoT devices
Consistent user experience
Strengthened security of connected devices
Identification and rectification of issues at early stages
Averted cost failures
Machine Learning and Artificial Intelligence (AI)
The confluence of Machine Learning (ML) and Artificial Intelligence (AI) occurs in recognising, analysing, and interpreting patterns and methods in data to facilitate reasoning and decision-making beyond human intervention. This field of computational science can be used to ensure the quality of software throughout the stages of development.
Amongst the deluge of fields, ML and AI’s role in QA ranges from complete monitoring of API testing, identification of the method and timeline of running a script, laying the foundation for better data analysis using spidering tools, to comprehensive monitoring of testing operations.
However, there are several hindering factors that affect the prominence of ML and AI as far as QA is concerned, such as the lack of expertise and skills shortage in test design, strategy, data setup, etc. Furthermore, while the benefits of ML and AI in QA are manifold, the initial implementation costs nothing less than a small fortune.
Irrespective, the benefits outweigh the risks and costs in the following areas:
Why Should Your Company Adopt ML and AI?
A gained competitive edge with sped-up testing procedures
Precise definition of bottlenecks for root cause analysis
Prediction of software defects
Improved tests’ resilience to the dynamic environment
Streamlined visual testing
Robotic Process Automation (RPA)
As opposed to the traditional test automation techniques, Robotic Process Automation (RPA) replicates user processes and actions. Decisions are taken by leveraging the cognitive abilities of RPA to replicate the actions of a human.
Furthermore, integration between multiple applications across different technologies through manual testing can prove to be a bottleneck. This can be solved with RPA’s task-based automation that automates steps to create test data sets covering all the platforms.
Over and above that, the integration of RPA in User Acceptance testing helps in validating the end-to-end business processes. The simplified workflow and task-based automation reduce the testing time and costs for the project.
Why Should Your Company Adopt Robotic Process Automation (RPA)?
Enabled optimisation with reusable automation libraries
Eliminated mundane QA tasks
Monitoring and scheduling automated tests
Reusable test data for consistent and continuous QA