The Changelog: Software Development, Open Source Why you shouldn't use AI to write your tests (News)
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May 28, 2024 The discussion kicks off with a critical look at the drawbacks of using AI for test writing, emphasizing the need for more nuanced testing approaches. Delving into the dark side of the web, it highlights the alarming prevalence of broken links and the eerie 'zombie internet' phenomenon. The conversation then shifts to the paradox of clear code, revealing the hidden challenges behind writing readable code and how it can impact professional recognition. Anecdotes add a personal touch, making complex issues relatable and engaging.
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AI for Testing
- Don't use AI to write low-level tests derived from implementation.
- Focus on higher-level integration or end-to-end tests that validate user interactions and features.
Test-Driven Design
- Writing the right tests is crucial, and often determines implementation design.
- Once tests are defined, implementation can become trivial, possibly even automated.
AI for Implementation
- Consider leveraging AI for implementation code generation.
- Focus on writing comprehensive tests and allowing AI to handle the corresponding code.