Emergence of AI in software testing process:
Any organisation in this digital world which build and develop software, delivering a quality product is their utmost priority and this should be done on faster release cycles. This can only be achieved through test automation. On the emergence of test automation, lot of tools and test automation frameworks came in place requiring QA specialists to write code to test code written by developers. This test automation frameworks also had some limitations like requiring long configurations and constant human intervention to improve tool performance, continuous maintenance of test scripts and to ensure comprehensive test coverage issues.
To overcome above challenges, the role of Artificial Intelligence (AI) is becoming increasingly prominent in software development life cycle. In the advent of new AI technologies, testing process has taken a new face by enabling faster, more reliable and effective software releases.
Role of AI in Software testing process:
Definition: “AI refers to computer systems designed to mimic human cognitive abilities which typically require human intelligence such as visual perception, speech recognition, decision making and translation between languages.”
AI in software testing process transformed from traditional heuristic algorithmic approach to self-evolving and self-improving process which enables continuous software development. AI not only identifies the root cause of the problem but also helps developers identify the exact piece of code that has the issue.
Usage: AI can be used for following in software testing process
- To analyse massive amount of data to detect patterns, generate optimised & critical test cases.
- To automatically update test cases based on the continuous product changes and ensure test coverage.
- To identify how real business or general users interact with the application and automatically generate tests that simulate user journeys and workflows.
- To increase the test efficiency by automating test data creation there by eliminating manual data creation.
Benefits of AI in Software testing process:
- Low code testing: AI provides the capability for non-technical users who does not having programming skills to generate automated tests simply by performing the desired steps on application under test. This will then create a reusable test script which can be run multiple times. Low code testing enables to expand the automated testing across the organisation.
- Low maintenance testing: As we know application/product functionality keeps changing day-to-day, it has become overhead and expensive to maintain the automated tests. AI proactively analyses the product changes and will assist testing teams to intelligently update the test cases. This predictive and proactive approach helps companies to stay ahead of maintenance and deliver high quality user experiences.
- Improve test case prioritization: Using AI, test cases can be prioritized based on parameters like criticality and past defect areas. AI can be used to analyse historical test results and product usage data to determine which test cases are critical to the business and prioritisation.
- Improve accuracy and user experience: AI eliminates human errors and speeds up the testing process. By simplifying the testing process and able to identify potential bugs before releasing the product into market will enable better user experience.