What is Smart or Intelligent Test Automation?
Intelligent Test Automation may be a blend of ML, AI processes, and traditional automation practices that make automation more stable and efficient.It employs artificial intelligence methods to aid in automatic script generation, bug prediction, and coverage improvement. This perfect mix leads to intelligent processes which have low to no error rate and high efficiency.
Features of Smart Test Automation Tool
(a) Scriptless test creation and execution â€“ Smart Test Automation tools offer an intuitive interface that permits anyone with no code or limited knowledge to create and manage tests quickly.
(b) Rapid test creation â€“ Allows easy automation of test cases written in plain-Text English by using tongue Processing (NLP)
(c) Reusable methods â€“ Smart tools allow you to reuse the steps you've got created before to test the scripts.
(d)Cloud Execution Platforms â€“ With Integration to the Cloud Execution Platforms, test automation tools allow you to perform tests within the cloud using different browsers and multiple operating system combinations.
(e)Unified Platform â€“ An intelligent test automation tool allows you to automate the test cases for multiple platforms- desktop, web, mobile, tablets, etc., from one place. Thus, managing tests become easier.
(f) Fast Debugging â€“ Test Automation tool allows easy integration with bug tracking tools that facilitate your report bugs and track the status seamlessly. It directly pushes failed test cases to the Defect Tracking Tools together with the captured screenshots.
(g) Auto-healing â€“ Intelligent test automation features a peculiar feature of self-healing. Whenever there's a change in function or object property, the test automatically updates itself and doesn't fail during execution.
(h) Smart Validation â€“ Validates results with a mixture of AI and a proprietary algorithm. It helps company and people data clean by removing invalid data, errors, or formatting issues.
(i) Intelligent reporting and analytics â€“ Test automation tools have smart, robust reporting features like log analytics, risk-based, predictive analytics, etc.
(j) Log Analytics : Intelligently identify critical errors/failures supported the logs generated and, if necessary, log defects within the Project management tool.
(k) Predictive Analytics : Estimate key parameters and specifications of end-customer behaviors and find out app areas to concentrate on.
(l) Prognosis Analytics : Utilize the prevailing customer data and analytics data to determine how usersâ€™ demands and browsing behaviors will evolve in the future.
Benefits of Intelligent Test Automation
Intelligent Test Automation can provide substantial benefits to organisations, including:
1. Increase in test coverage
2. Automatic generate test cases and test scripts, using machine learning
3. Codeless automation
4. Faster and stable UI tests
5. Smart predictive analytics
6. Defect prediction supported historical data and failures
7. Faster reaction time , Root cause analysis, and Infrastructure optimization
8. Automated test data management
9. Automated test environment generation
10.Automatic and smart prioritization of test cases within a reusable framework
Future Use Cases
Some of the interesting case scenarios where Natural Language Programming, AI , and Machine learning are often a game-change are:
(a) Test Recommendation Engine: AI can help identify the test cases that ought to run in case of any code change in the application. AI also can determine the tests that can fix the codes and run only those scripts instead of running the entire suite. Hence, this may reduce the testing teamsâ€™ manual efforts in identifying the tests to be run for quick bug fixes.
(b)Learning by Observing User Patterns: AI are often leveraged by identifying the common user patterns across multiple user journeys. supported these patterns, AI and ML engines can generate reusable components which will be used across various test scripts, thus reducing the scripting efforts of the testing team.
(c)Handling Response Time: The more the test runs by the user, the more the info AI collects and the steadier the tests. supported server responses, AI can optimize the wait time for the automation scripts to accommodate different page load times within the application.
(d)Dynamic Locators: With the use of dynamic locators and multiple attributes for the same element, AI will prevent the failure of tests. no matter the buttonâ€™s name change, it can easily choose the subsequent best attribute to locate the element.
Future of Intelligent Test Automation
Undoubtedly, Intelligent Test Automation and Analytics will make an enormous impact on the testing phase of Software development. The intelligent test automation increases the test coverage and prioritizes the main target areas, tests to be run, and detects the high-risk areas. Organizations should leverage these AI benefits to optimize the standard lifecycle of the product at every stage and deliver the project on parameters of high agility and efficiency.