Consider the following pseudo code1. Begin2. Read Gender3. __Print ''Dear''4. If Gender = 'female'5. Print (''Ms'')6. Else7. __Print ( ''Mr'')8. Endif9. EndHow many test cases are needed to achieve 100 per cent decision coverage?
I've got it! We need three test cases - one for 'female', one for 'male', and one for some other value of 'Gender' to make sure the code handles that case correctly. That should give us 100% decision coverage.
Wait, I'm a bit confused. Do we need to consider any other possible values for 'Gender' besides 'female' and 'male'? I want to make sure I'm not missing anything.
I'm not convinced this is the best approach. Automating tasks is one thing, but sharing knowledge articles might require a more robust solution. I'll need to explore other options to ensure we meet all the requirements.
Hmm, I'm a bit unsure about this one. The options seem similar, but I think the key is understanding what "explicit opt-in" means in the context of mobile marketing. I'll need to think this through carefully.
Okay, I've got this. Life insurance is commonly used for estate planning, business continuity, and replacing income - the options seem to cover those main uses. I just need to identify the one that doesn't fit.
Ben
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