General Discussion
1. Accelerating Timelines
• Instead of going through thousands of lines of code, as manual testers have to do, AI can quickly sort through log files, scan code in seconds, and detect errors in much less time.
• Additionally, AI does not get exhausted or make human errors, thus yielding more accurate results.
• By incorporating AI into repetitive tests, QA engineers can focus on testing new features or paying particular attention to the software’s essential parts.
2. Better Automation
As mentioned above, a large part of a QA’s job is to ensure that new code does not destabilize existing functional code. As more features are developed and added, the amount of code to be tested expands and can overwhelm already-burdened QA engineers.
• AI bots, on the other hand, will be able to evolve with changes in the code.
• They can adapt and learn to identify new functions.
• When AI bots identify a modification to the code, they can be programmed to decide if it is a new feature or some defect emerging from changes to the code.
• It is also possible to improve automated testing by utilizing a built platform.
3. Clarity on Client Requirements
In the realm of software testing, being able to understand what the client wants is of paramount importance.
• Using AI in software testing, examining similar websites and apps to determine what contributes to success among the target audience is possible.
• AI can help study competing products to identify key selling points so that developers and testers know what users want from a particular software.
• Testers can use AI to detect common code flaws that might hinder a software system’s flawless functioning.
• By understanding what the client wants, they can create test cases to ensure the product does not break when achieving those goals.
4. Mastering Test Automation with ChatGPT
As part of the automation testing trends in 2023, ChatGPT has taken the world by storm. Regarding AI for software testing, OpenAI is a state-of-the-art language model using natural language processing-based artificial intelligence that allows for the automation of tasks.
It can generate text in different formats, such as structured data, code snippets, and annotations, which can be used to automate tasks such as code generation and testing.
ChatGPT for test automation can be used for:
• Code Generation: it can generate code snippets based on natural language prompts, providing an excellent way for beginners to learn a programming language’s basic syntax and structure.
• Code Completion can be used to complete partially written code, assisting with the next steps.
• Code Explanation: it can be used to explain the purpose and function of specific lines of code, helping beginners and experts alike.
https://www.browserstack.com/guide/ai-with-software-testing
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