Artificial intelligence (AI) and machine learning (ML) are transforming multiple sectors of the economy and impacting several aspects of our daily lives. We can define those sectors like this, Workplaces such as those in finance, healthcare,retail, education. In our homes, AI is powering television and movie recommendations, personal digital assistants, security cameras, and home automation.

So when AI came for the Software testing it focus to make testing smarter and more efficient. AI and machine learning apply reasoning and problem solving to automate and improve testing. AI in software testing helps reduce time-consuming manual testing.

When AI and Testing are combined "It seems that just like AI needs testing, testin needs AI.

Integrating Artificial Intelligence in Testing

  • Generating Unit Tests: The simplest use case for applying AI in software testing is generating unit tests. AI can help with the static analysis of the software to decide which areas of the code are not covered by unit tests. The tool can use this information to create unit tests for uncovered code and even provide input for these unit tests. It’s easier for an AI-assisted tool to create unit tests, as these types of tests don’t need any setup or interactions with additional components.

  • UI Testing: In automation testing, Artificial Intelligence can be used in the object application classification for all user interfaces. The recognized controls are categorized when you create the tools and testers can pre-train controls that are usually seen in out-of-the-box setups. When the hierarchy of controls is identified the testers can create a technical map such that the AI is looking at the Graphical User Interface (GUI) to acquire labels for the different controls.

AI-based Test Automation Tools

  • Testimo io
  • Appvance
  • Test.ai
  • Functionize
  • Applitools Eye
  • AutonomIQ
  • Mabl
  • Parasoft SOAtest

Integrating AI in Software Testing Advantages

  • Improved accuracy
  • Going beyond the limitations of manual testing
  • Helps both developers and testers
  • Increase in overall test coverage
  • Saved time and money with high performance
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