Bottom-Up Parsers: A Survey

This study offers a thorough analysis of bottom-up parsing techniques, necessary for the creation and execution of compilers. Parsers such as SLR (Simple LR), LR (Canonical LR), LR(k) and LALR (Look-Ahead LR) are bottom-up and known for their efficiency and robustness in constructing parse trees from root to leaves during syntax analysis. This paper follows the evolution throughout history, theoretical bases, and real-world uses of these parsers. We examine the formal characteristics, contrast different bottom-up parsing methods, and investigate advanced subjects like error handling and optimization techniques. Furthermore, there is a review of recent developments and upcoming research paths in bottom-up parsing to provide a comprehensive grasp of their significance in syntactic analysis.

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Publication Details

Published
2024-11-07
DOI
https://doi.org/10.1109/csitss64042.2024.10816907
Primary Topic
Algorithms and Data Compression
Type
article
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article

Bottom-Up Parsers: A Survey

A. Karthik, Meena Belwal, B Venkat Vinod Kumar, Bejji Bharadwaj Sree Sai Karthikeya
Algorithms and Data Compression
article

Bottom-Up Parsers: A Survey

A. Karthik, Meena Belwal, B Venkat Vinod Kumar, Bejji Bharadwaj Sree Sai Karthikeya
article en

Abstract

This study offers a thorough analysis of bottom-up parsing techniques, necessary for the creation and execution of compilers. Parsers such as SLR (Simple LR), LR (Canonical LR), LR(k) and LALR (Look-Ahead LR) are bottom-up and known for their efficiency and robustness in constructing parse trees from root to leaves during syntax analysis. This paper follows the evolution throughout history, theoretical bases, and real-world uses of these parsers. We examine the formal characteristics, contrast different bottom-up parsing methods, and investigate advanced subjects like error handling and optimization techniques. Furthermore, there is a review of recent developments and upcoming research paths in bottom-up parsing to provide a comprehensive grasp of their significance in syntactic analysis.

Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 77%
Algorithms and Data Compression
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