The rotation of multi-dimensional arrays, or tensors, is a fundamental operation in computer science with applications ranging from data processing to scientific computing. While various methods exist, achieving this rotation in-place (i.e., with O(1) auxiliary space) presents a significant algorithmic challenge. The elegant three-reversal algorithm provides a well-known O(1) space solution for one-dimensional arrays. This paper introduces a generalization of this method to N dimensions, resulting in the “ reversal algorithm”. This algorithm achieves in-place tensor rotation with O(1) auxiliary space and a time complexity linear in the number of elements. We provide a formal definition for N-dimensional tensor reversal, present the algorithm with detailed pseudocode, and offer a rigorous proof of its correctness, demonstrating that the pattern observed in one dimension ( reversals) and two dimensions ( reversals) holds for any arbitrary number of dimensions.

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