{"title":"Enhancing XML-based Compiler Construction with Large Language Models: A Novel Approach","authors":"Idrees A. Zahid, Shahad Sabbar Joudar","doi":"10.58496/mjbd/2024/003","DOIUrl":null,"url":null,"abstract":"Considering the prevailing rule of Large Language Models (LLMs) applications and the benefits of XML in a compiler context. This manuscript explores the synergistic integration of Large Language Models with XML-based compiler tools and advanced computing technologies. Marking a significant stride toward redefining compiler construction and data representation paradigms. As computing power and internet proliferation advance, XML emerges as a pivotal technology for representing, exchanging, and transforming documents and data. This study builds on the foundational work of Chomsky's Context-Free Grammar (CFG). Recognized for their critical role in compiler construction, to address and mitigate the speed penalties associated with traditional compiler systems and parser generators through the development of an efficient XML parser generator employing compiler techniques. Our research employs a methodical approach to harness the sophisticated capabilities of LLMs, alongside XML technologies. The key is to automate grammar optimization, facilitate natural language processing capabilities, and pioneer advanced parsing algorithms. To demonstrate their effectiveness, we thoroughly run experiments and compare them to other techniques. This way, we call attention to the efficiency, adaptability, and user-friendliness of the XML-based compiler tools with the help of these integrations. And the target will be the elimination of left-recursive grammars and the development of a global schema for LL(1) grammars, the latter taking advantage of the XML technology, to support the LL(1) grammars construction. The findings in this research not only underscore the signification of these innovations in the field of compilation construction but also indicate a paradigm move towards the use of AI technologies and XML in the context of the resolution of programming traditional issues. The outlined methodology serves as a roadmap for future research and development in compiler technology, which paves the way for open-source software to sweep across all fields. Gradually ushering in a new era of compiler technology featuring better efficiency, adaptability, and all CFGs processed through existing XML utilities on a global basis.","PeriodicalId":325612,"journal":{"name":"Mesopotamian Journal of Big Data","volume":" 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mesopotamian Journal of Big Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58496/mjbd/2024/003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Considering the prevailing rule of Large Language Models (LLMs) applications and the benefits of XML in a compiler context. This manuscript explores the synergistic integration of Large Language Models with XML-based compiler tools and advanced computing technologies. Marking a significant stride toward redefining compiler construction and data representation paradigms. As computing power and internet proliferation advance, XML emerges as a pivotal technology for representing, exchanging, and transforming documents and data. This study builds on the foundational work of Chomsky's Context-Free Grammar (CFG). Recognized for their critical role in compiler construction, to address and mitigate the speed penalties associated with traditional compiler systems and parser generators through the development of an efficient XML parser generator employing compiler techniques. Our research employs a methodical approach to harness the sophisticated capabilities of LLMs, alongside XML technologies. The key is to automate grammar optimization, facilitate natural language processing capabilities, and pioneer advanced parsing algorithms. To demonstrate their effectiveness, we thoroughly run experiments and compare them to other techniques. This way, we call attention to the efficiency, adaptability, and user-friendliness of the XML-based compiler tools with the help of these integrations. And the target will be the elimination of left-recursive grammars and the development of a global schema for LL(1) grammars, the latter taking advantage of the XML technology, to support the LL(1) grammars construction. The findings in this research not only underscore the signification of these innovations in the field of compilation construction but also indicate a paradigm move towards the use of AI technologies and XML in the context of the resolution of programming traditional issues. The outlined methodology serves as a roadmap for future research and development in compiler technology, which paves the way for open-source software to sweep across all fields. Gradually ushering in a new era of compiler technology featuring better efficiency, adaptability, and all CFGs processed through existing XML utilities on a global basis.
考虑到大型语言模型(LLMs)应用的普遍规律以及 XML 在编译器方面的优势。本手稿探讨了大型语言模型与基于 XML 的编译器工具和先进计算技术的协同整合。这标志着在重新定义编译器构建和数据表示范式方面取得了重大进展。随着计算能力的提高和互联网的普及,XML 成为表示、交换和转换文档与数据的关键技术。本研究以乔姆斯基的上下文自由语法(CFG)为基础。我们认识到它们在编译器构建中的关键作用,通过开发一种采用编译器技术的高效 XML 解析器生成器,解决并减轻与传统编译器系统和解析器生成器相关的速度问题。我们的研究采用了一种有条不紊的方法来利用 LLM 和 XML 技术的复杂功能。 关键在于实现语法优化自动化、促进自然语言处理能力以及开创先进的解析算法。为了证明其有效性,我们进行了全面的实验,并将其与其他技术进行了比较。这样,在这些集成的帮助下,基于 XML 的编译工具的效率、适应性和用户友好性就会得到关注。我们的目标将是消除左递归语法,并为 LL(1) 语法开发一个全局模式,后者将利用 XML 技术来支持 LL(1) 语法的构建。这项研究的成果不仅强调了这些创新在编译构建领域的意义,还表明了在解决编程传统问题的背景下使用人工智能技术和 XML 的范式。概述的方法论为编译器技术的未来研究与发展提供了路线图,为开源软件横扫各个领域铺平了道路。编译器技术将逐渐迎来一个新时代,其特点是效率更高、适应性更强,所有的 CFG 都能通过现有的 XML 工具在全球范围内进行处理。