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A Top-Down Three-Way Merge Algorithm for HTML/XML Documents

  • Conference paper
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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1228))

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Abstract

Collaborative work, with the need to keep HTML/XML code up-to-date, is now becoming vital particularly in the Web Development field. In order to fully support collaborative work and resolve related problems the need has arisen for an optimum solution to the automated editing of a number of parallel copies originating from a single original HTML/XML code document with the additional requirement to subsequently merge the copies into a single updated document. A number of algorithms have been used in the past for the purpose, such as: Diff3, XmlDiff, DeltaXML & 3DM, but HTML/XML code complexity related issues have now called for an algorithm that is more specifically designed for the purpose. In this paper a new algorithmic approach to merging HTML/XML code documents is presented that is based on the “Three-way Merge” approach and the “Node-per-Node” comparison between ordered trees. For the creation of the actual merging function operating at the heart of the algorithm, a particular methodology was followed in which only the two “Current Versions” are required for the generation of the updated document, and no involvement of the “Original Document” is necessary. This is an important improvement over the currently existing algorithms because eliminates the well-known “Idempotent” problem in merging two HTML/XML documents. In addition, the algorithmic approach presented here allows for the identification and treatment of all the conflicts that arise during a HTML/XML code merging in an ordered and clearly specified manner.

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Acknowledgment

The authors would like to thank editors and anonymous reviewers for their valuable and constructive suggestions on this paper.

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Correspondence to Anastasios G. Bakaoukas .

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Bakaoukas, A.G., Bakaoukas, N.G. (2020). A Top-Down Three-Way Merge Algorithm for HTML/XML Documents. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1228. Springer, Cham. https://doi.org/10.1007/978-3-030-52249-0_6

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