Debugging Round: Identify and Fix Bugs in a Multi-Component System

Question

**Format:** Live debugging round — you are given a codebase with several interconnected bugs across a data pipeline. You must diagnose each bug, explain the root cause, and apply a fix.

**Bug 1 — Off-by-one in pagination:**
```python
def paginate(items, page, page_size):
    start = page * page_size       # Bug: page=1 should start at index page_size
    return items[start:start+page_size]
# Fix: start = (page - 1) * page_size
```

**Bug 2 — Mutable default argument:**
```python
def append_event(event, history=[]):  # Bug: shared across all calls
    history.append(event)
    return history
# Fix: def append_event(event, history=None): history = history or []
```

**Bug 3 — Silent exception swallowing:**
```python
try:
    result = process(data)
except Exception:
    pass  # Bug: hides all errors, downstream uses stale result
# Fix: at minimum log the exception; re-raise or set result=None and handle
```

**Bug 4 — Race condition in cache update:**
```python
if key not in cache:
    cache[key] = fetch(key)  # Bug: two threads can both enter this branch
# Fix: use a lock or atomic setdefault / cache library with locking
```

## Follow-ups

1. How would you write a regression test for the mutable default argument bug?
2. What linting tools catch these categories of bugs automatically in Python?
3. How would you set up structured logging so silent exception swallowing is impossible by convention?
4. What is the difference between a race condition and a deadlock? Give an example of each.

Debugging Round: Identify and Fix Bugs in a Multi-Component System

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