Solve the Hard-level Merge K Sorted Lists coding interview problem online in Python & JavaScript. Run your code against real test cases in the browser and study worked examples. It covers linked list, heap, priority queue, and divide and conquer. Read the step-by-step solution and complexity analysis. Java starter code is also included for reference (no in-browser JVM yet, so it can't be run here).

Merge K Sorted Lists – Solve Online in Python & JavaScript

Find Median from Data Stream

Network Delay Time

Merge k sorted sequences using a heap of current candidates.

Each row in `lists` serializes one sorted linked list. Return the values of the merged sorted list. Solve with the same one-current-node-per-list heap used for real ListNode chains.

## Example
```json
Input: {"lists":[[1,4,5],[1,3,4],[2,6]]}
Output: [1,1,2,3,4,4,5,6]
```

## Constraints
- 0 <= k <= 10000
- 0 <= total values <= 10000
- Each input list is sorted

## Follow-up
How would the heap entries change if inputs were actual ListNode heads?

The key pattern is: A min-heap retains one current value from each list. Identify the state and invariant before coding.

Recognize the Pattern

Advance one state transition at a time. Mark or update state before exploring dependent work.

Build the Algorithm

Test empty or minimal input, skewed shapes, duplicates where allowed, and impossible outcomes.