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    ARTICLE

    Performance Enhancement of XML Parsing Using Regression and Parallelism

    Muhammad Ali, Minhaj Ahmad Khan*

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 287-303, 2024, DOI:10.32604/csse.2023.043010

    Abstract The Extensible Markup Language (XML) files, widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications. With the existing Document Object Model (DOM) based parsing, the performance degrades due to sequential processing and large memory requirements, thereby requiring an efficient XML parser to mitigate these issues. In this paper, we propose a Parallel XML Tree Generator (PXTG) algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework (RXPF) that analyzes and predicts performance through profiling, regression, and code generation for efficient parsing. The PXTG algorithm… More >

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