The Product of Two Run-Length Encoded Arrays problem gives you two arrays in run-length encoding format (value, count pairs) and asks you to compute their element-wise product, returned as a run-length encoded array. This coding problem uses a two-pointer merge on the encoded formats. The array and two pointers interview pattern is demonstrated.
Yandex and Meta ask this because it tests the ability to process run-length encoded data without decoding — a technique used in image compression, genomics, and data streaming. The two-pointer approach merges runs while tracking remaining counts.
Two-pointer on encoded arrays. Maintain pointers i, j for encoded1 and encoded2. At each step: compute product of current values. Take count = min(encoded1[i][1], encoded2[j][1]). Append (product, count) to result (merging with previous if same product). Reduce counts: encoded1[i][1] -= count; if 0, advance i. Same for j.
encoded1=[(1,3),(2,3)], encoded2=[(6,3),(3,3)].
Run-length encoded operations require processing chunks without full decoding. The two-pointer merging approach is O(n+m) where n,m are numbers of runs — much better than O(decoded length). Practice similar encoded array operations: "add/subtract two RLE arrays," "multiply two RLE arrays." The key insight: take the minimum chunk size from both arrays at each step, advancing whichever run is exhausted.
| Title | Difficulty | Topics | LeetCode |
|---|---|---|---|
| Remove Duplicates from Sorted Array II | Medium | Solve | |
| Next Permutation | Medium | Solve | |
| Find Indices With Index and Value Difference II | Medium | Solve | |
| Maximum Product of First and Last Elements of a Subsequence | Medium | Solve | |
| Number of Subarrays with Bounded Maximum | Medium | Solve |
