QA Testing for Vibecoded Booking Apps

Availability is the foundation of any booking system and must be completely accurate. Testers verify that available time slots reflect the provider's actual schedule, that booked slots are immediately removed from availability, and that buffer times between appointments are respected. AI-generated scheduling logic frequently has race condition bugs where two users can book the same slot simultaneously, or where cancelling a booking does not properly restore the time slot to availability.

Timezone handling is one of the most error-prone areas in booking apps. Testers verify that time slots are displayed in the user's local timezone, that booking confirmations show the correct time for both parties, and that availability calculations work correctly across timezone boundaries. They test edge cases like booking across daylight saving time transitions, where a one-hour appointment might span the clock change, and verify that recurring availability rules account for timezone differences.

Real-world bookings rarely go as planned. Testers verify the complete modification lifecycle: rescheduling to a different time, changing the service type, adding or removing participants, and cancelling entirely. AI-generated booking systems often handle the initial booking well but have bugs in modification flows — rescheduling a booking might not release the original time slot, or changing the service type might not update the price.

Cancellation policies add business logic that must be enforced correctly. Testers verify that cancellation deadlines are enforced, that refund amounts calculate correctly based on how far in advance the cancellation is made, and that both the provider and customer receive appropriate notifications. They also test no-show handling and verify that the system correctly processes any associated fees or penalties.

Booking payments often involve deposits, full prepayment, or pay-at-service models, and the system must handle each correctly. Testers verify that the correct payment amount is charged based on the selected service and any applicable discounts, that deposit amounts are accurate, and that the remaining balance is correctly calculated and communicated. AI-generated payment integrations often charge the wrong amount when services are modified after initial booking.

Confirmation and reminder flows are essential for reducing no-shows. Testers verify that booking confirmations are sent immediately via the configured channels — email, SMS, or push notification — with accurate details including date, time, location, and any preparation instructions. They also check that reminder notifications are sent at the correct intervals before the appointment and that calendar invite attachments contain the right information and timezone.