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**In short:**
A **base case** is the condition at which a recursive function **stops calling itself** and **returns the result immediately**. It stops the recursion.

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### Detailed explanation

In recursion, a task is divided into smaller subtasks of the same type. For the recursive process not to be infinite, it needs a **stopping point** - the base case. When the input reaches this "boundary of simplicity", the function **does not make a recursive call** and instead returns the ready value.

**Signs of a good base case:**

1. **Unambiguity** - it is easy to tell that dividing the task further makes no sense.
2. **Completeness** - the base case covers the real "edge" inputs.
3. **Reachability** - every recursive step brings the arguments closer to the base case.

**Examples:**

- Factorial:

```javascript
function factorial(n) {
  if (n === 0) return 1;          // base case
  return n * factorial(n - 1);    // recursive step
}
```

- Array traversal:

```javascript
function sum(arr, i = 0) {
  if (i === arr.length) return 0; // base case: empty tail
  return arr[i] + sum(arr, i + 1);
}
```

- Tree search:

```javascript
function find(node, target) {
  if (!node) return null;                  // base: empty branch
  if (node.value === target) return node;  // base: found
  return find(node.left, target) || find(node.right, target);
}
```

**Common mistakes:**

- No base case -> infinite recursion and stack overflow.
- A base case exists, but **the recursive step does not shrink the task** (does not approach the base).
- Incomplete base case (does not account for `0`, an empty array, `null`, etc.).

**Tips:**

- First state the base case in words, then code it.
- Check that every recursive call makes the input "simpler".
- For several "edges" (for example, `n < 0`, `n === 0`, `n === 1`), define **several base cases**.

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