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The two pointers technique is a common interview pattern for reducing nested-loop scans into linear-time solutions on arrays and strings. Interviewers expect you to recognize when sequential structure allows two indices to move intelligently.
Explain how you would solve a two pointers problem on an array or string.
Your answer should address:
Go beyond a definition. The interviewer expects you to describe the intuition, common use cases, complexity trade-offs, and a few representative examples such as palindrome checking, pair sum in a sorted array, or removing duplicates in place.
Two indices start at the left and right ends of an array or string and move toward each other. This pattern works well when decisions can be made by comparing boundary values, such as palindrome checks or pair sums in sorted arrays.
left, right = 0, len(s) - 1
while left < right:
if s[left] != s[right]:
return False
left += 1
right -= 1
Both pointers move from left to right, but at different speeds or roles. One pointer often scans input while the other tracks the write position, window start, or last valid boundary.
write = 1
for read in range(1, len(nums)):
if nums[read] != nums[read - 1]:
nums[write] = nums[read]
write += 1
A sliding window is a specialized two-pointer approach where one pointer expands a range and the other shrinks it to maintain a condition. It is common for substring and subarray problems involving length, sum, or distinct elements.
left = 0
for right in range(len(s)):
# expand window
while invalid_window:
left += 1
Two pointers only help when pointer movement can safely discard part of the search space or maintain a useful invariant. Sorted input, monotonic conditions, and contiguous ranges are strong signals that the technique applies.
A good two-pointer solution maintains a rule that stays true after every pointer update, such as 'the current window satisfies the constraint' or 'all values before write are processed correctly.' Invariants make the algorithm correct and easier to explain in interviews.