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AI and ML change software testing. Old ways are slow. New tools find bugs faster.
Benefits for your QA process:
- Faster tests. AI runs tests in parallel. You get feedback fast.
- Less manual work. AI handles routine tasks.
- Lower costs. Tests run without people.
- Better bug detection. ML finds patterns. You fix bugs before users see them.
Challenges to watch:
- Hard setup. AI needs data and skill.
- Hard to understand. Models hide their logic.
- Errors. AI flags wrong bugs. It misses real ones.
- Constant work. AI tools need updates.
Best practices for you:
- Set goals. Decide what you want. Pick speed or fewer bugs.
- Use a hybrid model. Let AI do boring work. You do the thinking.
- Start small. Pick high-impact tasks. Automate large suites first.
Use these tools. Deliver quality software faster.
Source: https://dev.to/anna17/ai-and-ml-in-software-testing-how-these-technologies-are-transforming-qa-7pd Optional learning community: https://t.me/GyaanSetuAi