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An efficient algorithm for ${\mathrm{\LaTeX}}$ documents comparing

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The problem is constructing the differences that arise on ${\mathrm{\LaTeX}}$ documents editing. Each document is represented as a parse tree whose nodes are called tokens. The smallest possible text representation of the document that does not change the syntax tree is constructed. All of the text is splitted into fragments whose boundaries correspond to tokens. A map of the initial text fragment sequence to the similar sequence of the edited document corresponding to the minimum distance is built with Hirschberg algorithm A map of text characters corresponding to the text fragment sequences map is cunstructed. Tokens, that chars are all deleted, or all inserted, or all not changed, are selected in the parse trees. The map for the trees formed with other tokens is built using Zhang–Shasha algorithm.

Keywords: automation, editing distance, text analysis, lexeme, machine learning, metric, parse tree, syntax tree, token, ${\mathrm{\LaTeX}}$
Citation in English: Chuvilin K.V. An efficient algorithm for ${\mathrm{\LaTeX}}$ documents comparing // Computer Research and Modeling, 2015, vol. 7, no. 2, pp. 329-345
Citation in English: Chuvilin K.V. An efficient algorithm for ${\mathrm{\LaTeX}}$ documents comparing // Computer Research and Modeling, 2015, vol. 7, no. 2, pp. 329-345
DOI: 10.20537/2076-7633-2015-7-2-329-345
• . Machine learning approach to automated correction of ETgX documents. — 2016. — P. 33.
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International Interdisciplinary Conference "Mathematics. Computing. Education"

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