Computational Stemma Reconstruction

Computational stemma reconstruction borrows the mathematics of biological phylogenetics to rebuild the family tree of a manuscript tradition automatically from coded variant readings. Each surviving witness is treated as a taxon and each place of textual variation as a character with discrete states, exactly as a biologist treats species and the genes that vary among them. Tree-inference algorithms then search for the genealogy that best explains the observed pattern of variants, typically the tree requiring the fewest reading changes (maximum parsimony) or the most probable tree under an evolutionary model. Teemu Roos and Tuomas Heikkilä's 2009 study established how to evaluate these methods rigorously, building artificial manuscript traditions with a known true stemma and measuring how accurately each algorithm recovered it. The result is a scalable, reproducible complement to the hand-built Lachmannian stemma.