Building calendaring and scheduling software is a notorious rite of passage in software engineering. What seems like a simple CRUD application (Create, Read, Update, Delete) quickly morphs into a horrific matrix of temporal logic, distributed systems, and geopolitical edge cases.

If you implement a scheduling tool naively, here is an enumeration of the bugs you are almost guaranteed to encounter.

1. The Timezone & DST Quagmire

Your example of Daylight Saving Time (DST) is just the tip of the iceberg. Naive implementations usually fail here in a few spectacular ways:

• The “Offset vs. Zone” Trap: Storing a user’s timezone as a fixed offset (e.g., UTC-5) rather than an IANA timezone ID (e.g., America/New_York). Offsets change twice a year; IANA IDs handle this dynamically. If you store -5, when DST ends, your user’s 9:00 AM meetings will suddenly occur at 10:00 AM or 8:00 AM.
• The Ambiguous/Missing Hour: * Spring Forward: In March, the clock jumps from 1:59 AM to 3:00 AM. A naive system allowing a user to book a recurring meeting at 2:30 AM will crash or glitch on this day because that time does not exist.
  • Fall Back: In November, the clock repeats the 1:00 AM hour. If someone books a slot at 1:30 AM, a naive system won’t know if they mean the first 1:30 AM or the second 1:30 AM, potentially double-booking or shifting times.
• Geopolitical Fluidity: Governments change their DST rules constantly. If you hardcode rules instead of dynamically updating your timezone database (like the tz database), your software will break when a country decides to abandon DST on short notice.

2. Concurrency and the “Double-Booking” Race Condition

A naive scheduling flow looks like this:

1. User requests available slots.
2. Server queries DB: SELECT * FROM appointments WHERE slot = X.
3. Server sees the slot is empty and displays it.
4. User clicks “Book”.
5. Server saves the appointment.

• The Bug: If two different invitees open the same booking page simultaneously, they will both see the 10:00 AM slot as available. If they both click “Book” at the exact same millisecond, a naive implementation will execute step 2 for both users before step 5 finishes for either. Result: Both users get successfully booked for the exact same slot.
• Fix: This requires proper database isolation levels, pessimistic/optimistic locking, or atomic INSERT ... WHERE NOT EXISTS constraints.

3. The Recurring Event Drift

Handling an event that happens “every Tuesday at 9:00 AM” sounds simple, but computers think in absolute Unix timestamps (seconds since 1970).

• The Bug: If you calculate all future occurrences of a recurring event by simply adding $7 \times 24 \times 60 \times 60$ seconds (one week) to the initial timestamp, your event will permanently drift by an hour the moment the calendar crosses a DST boundary.
• The Leap Year Ghost: If an event is set to recur monthly on the 29th, 30th, or 31st, a naive system will break or skip months when it hits February or shorter months. If it’s a yearly event on February 29th, it will disappear for three years straight.

4. Buffer Time & Boundary Blunders

Calendly-like apps allow users to set “buffer times” (e.g., 15 minutes of free time before and after a meeting to breathe or take notes).

• The Overlapping Buffer: Suppose a host has a meeting from 10:00 AM to 10:30 AM with a 15-minute post-meeting buffer. The host is blocked until 10:45 AM. A naive implementation often forgets to check adjacent buffers, allowing an invitee to book a meeting at 10:35 AM because “10:35 is technically open,” completely violating the host’s buffer rules.
• The Midnight Crosser: If a host in Tokyo (UTC+9) has working hours set from 9:00 AM to 5:00 PM, and a user in New York (UTC-5) tries to book them, the available slots cross the calendar date boundary. Naive date arithmetic often fails to wrap around the day correctly, either showing the host as unavailable or offering slots on the wrong day.

5. The External Calendar Sync Loop of Doom

To be useful, your software must sync with Google Calendar, Outlook, and Apple Calendar. This introduces distributed systems chaos.

• The Infinite Sync Loop: Your app detects a new event in Google Calendar $\rightarrow$ your app updates its internal database $\rightarrow$ your app’s sync engine mistakenly flags this internal update as a “new event” $\rightarrow$ it pushes it back to Google Calendar $\rightarrow$ Google flags it as new… and suddenly your user has 5,000 duplicate events.
• The Webhook Lag Drop: Google Calendar uses webhooks to tell your app when a user modifies their calendar externally. Webhooks can fail, be delayed, or arrive out of order. If a user deletes a blocking event on Google and an invitee instantly tries to book that slot on your app before the webhook arrives, the booking will be erroneously blocked.

6. Cultural and Regional Assumptions

• The “Monday is Day 1” Fallacy: Hardcoding the week to start on Sunday or Monday. In the US, calendars usually start on Sunday. In Europe, Monday. In some Middle Eastern countries, the weekend is Friday/Saturday, meaning the workweek starts on Sunday. Naive UI/UX layout and backend logic for “working days” will alienate global users.

More build vs. buy material