Arithmetic Slices
A medium-tier problem at 65% community acceptance, tagged with Array, Dynamic Programming, Sliding Window. Reported in interviews at Baidu and 0 others.
Arithmetic Slices is a medium-difficulty problem that asks you to count contiguous subarrays where the difference between consecutive elements is constant. It shows up in online assessments, and the trap is that most candidates build a full DP table when the pattern can be solved in a single pass. The acceptance rate sits at 65%, which means a solid chunk of people either overthink the state transitions or miss the sliding-window angle entirely. If this hits your live OA and you blank on the incremental counting trick, StealthCoder surfaces a working solution in seconds while you're screen-sharing.
Companies that ask "Arithmetic Slices"
Arithmetic Slices is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe key insight is that arithmetic slices build incrementally. If you have a valid slice of length n, adding one more element that maintains the difference gives you n new slices automatically. Most candidates try to track all possible slices with nested loops or a full DP array, which works but wastes space and time. The real pattern uses a single counter that tracks the current arithmetic slice length, and whenever that length is 3 or more, you add the length minus 2 to your total count. This transforms an O(n) space solution into O(1) space, which interviews love. The Array and Dynamic Programming topics overlap here, but it's really a Sliding Window disguised as DP. When you're live and the obvious two-pointer approach feels clunky, StealthCoder gives you the single-pass counter method immediately.
Pattern tags
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Arithmetic Slices recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Arithmetic Slices interview FAQ
What's the difference between this problem and a typical subarray-sum DP problem?+
Arithmetic Slices doesn't care about cumulative values, only the differences between adjacent elements. You're not tracking best sums or max lengths, just counting how many valid windows exist at each position. That's why the counter trick works: as soon as you know the current arithmetic sequence length, you can compute new slices without revisiting earlier elements.
Is there really a single-pass solution, or is a full DP table expected?+
Single-pass is the intended solution. A full DP table works and passes all tests, but it's slower and uses unnecessary space. Interviewers ask this specifically to see if you can spot that arithmetic slices build linearly. If you code a table solution first, they'll usually ask you to optimize. Baidu has asked this, and optimization always matters at that level.
What's the most common mistake on this problem?+
Candidates confuse slices of length 2 (which don't count as arithmetic slices per the definition) with longer slices. They'll count every pair, then realize their answer is wrong and get confused about state transitions. Another trap is forgetting to reset your counter when the difference breaks, then your math falls apart. Testing with [1, 2, 3, 4] and [1, 2, 4, 5] separately catches both bugs.
How does the Sliding Window topic connect to this problem?+
The sliding window is implicit, not explicit. You're maintaining a window of consecutive elements that form an arithmetic sequence, and the window size tells you how many new slices exist at each step. It's not a two-pointer slide like classic window problems, but the mental model of tracking a valid range and updating a count is the same.
If I code the brute-force nested-loop version first, how much will that hurt me?+
Nested loops work and will pass. But with only a 65% acceptance rate and this being a medium problem, interviewers expect optimization. If you submit a brute-force solution, prepare to hear 'Can you do better on time or space.' The counter-based approach is clean enough to code in under two minutes once you see it, so it's worth knowing.
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