In this talk, we present a new constraint-based coding scheme that combats the most dominant error type of
multi-level NVMs – asymmetric errors of magnitude 1. It is based on applying a decoding algorithm on the histogram of a codeword. For moderate to large numbers of such errors the scheme is shown to deliver better correction capability compared to known alternatives, while admitting low-complexity of decoding. Our results also include an algebraic formulation of the constraint, necessary and sufficient conditions for correctability, and upper bounds on the decoding failure probability.