The Sliding Window Technique

If a problem asks for the longest or shortest contiguous run that satisfies something, it is a sliding window. That single recognition saves more time than any other pattern here.

The idea

Keep a start and an end index. Extend the end to grow the window. When the window breaks the rule, move the start until it is valid again. Each index moves forward at most once, so the whole scan is O(n) even though it looks like a nested loop.

Fixed window

When the size is given, slide it and adjust by one at each step.

function maxSumOfK(nums, k) {
  let sum = 0
  for (let i = 0; i < k; i++) sum += nums[i]

  let best = sum

  for (let i = k; i < nums.length; i++) {
    // Add the new element, drop the one that left.
    sum += nums[i] - nums[i - k]
    best = Math.max(best, sum)
  }

  return best
}

console.log(maxSumOfK([2, 1, 5, 1, 3, 2], 3))  // 9