What is the main concept behind merge sort?

Merge sort is primarily based on the concept of a multi-step process that amalgamates sorted lists. The algorithm functions by dividing an unsorted list into smaller sublists, each of which is individually sorted. The splitting continues recursively until the sublists are either empty or contain a single element, as these are inherently sorted.

Once the sublists have been sorted, the merge sort algorithm then systematically combines these sorted sublists back together into larger sorted lists. This merging process is where the "merge" in merge sort comes from, as it effectively merges smaller sorted sequences into a single sorted sequence.

The efficiency of merge sort lies in its ability to handle large datasets, leveraging the divide-and-conquer strategy. This method ensures that the overall process is efficient, typically operating at a time complexity of O(n log n), which is advantageous compared to more straightforward sorting algorithms, especially for large datasets.

Other options do not accurately capture the essence of merge sort's methodology. The focus on linear traversal, brute-force techniques, and binary search trees are not relevant to how merge sort specifically operates or achieves its sorting capabilities.