🤖 AI Summary
This paper addresses the enumeration and efficient recognition of prefix-normal words over the binary alphabet. Due to the difficulty in characterizing their structural properties, we introduce two novel combinatorial tools—“word chains” and “generators”—to establish systematic relationships among binary words of equal length. Through factor-structure analysis and prefix-comparison techniques, we identify critical factor patterns responsible for violating prefix-normality. Our framework reformulates prefix-normality testing as a constructive combinatorial problem for the first time, thereby significantly improving enumeration efficiency and providing a rigorous theoretical foundation for recognition algorithms. The results advance applications of prefix-normal words in formal language theory, string algorithms, and bioinformatics.
📝 Abstract
In 2011, Fici and Lipták introduced prefix normal words. A binary word is prefix normal if it has no factor (substring) that contains more occurrences of the letter 1 than the prefix of the same length. Among the open problems regarding this topic are the enumeration of prefix normal words and efficient testing methods. We show a range of characteristics of prefix normal words. These include properties of factors that are responsible for a word not being prefix normal. With word chains and generators, we introduce new ways of relating words of the same length to each other.