An Extensive Study on Text Serialization Formats and Methods
Wang Wei, Li Na, Zhang Lei, Liu Fang, Chen Hao, Yang Xiuying, Huang Lei, Zhao Min, Wu Gang, Zhou Jie, Xu Jing, Sun Tao, Ma Li, Zhu Qiang, Hu Jun, Guo Wei, He Yong, Gao Yuan, Lin Dan, Zheng Yi, Shi Li
TL;DR
The work addresses how to choose among text serialization formats for data storage and interchange by examining readability, representation capabilities, and performance. It surveys JSON, XML, YAML, and CSV, articulates serialization/deserialization workflows, and contrasts formats using hypothetical benchmarks to illustrate trade-offs. Key contributions include a structured comparison of format characteristics, a framework for evaluating performance versus human readability, and guidance on schema roles and ecosystem considerations. The practical impact lies in guiding developers and system architects to select appropriate text serialization strategies and informing future tooling and format design.
Abstract
Text serialization is a fundamental concept in modern computing, enabling the conversion of complex data structures into a format that can be easily stored, transmitted, and reconstructed. This paper provides an extensive overview of text serialization, exploring its importance, prevalent formats, underlying methods, and comparative performance characteristics. We dive into the advantages and disadvantages of various text-based serialization formats, including JSON, XML, YAML, and CSV, examining their structure, readability, verbosity, and suitability for different applications. The paper also discusses the common methods involved in the serialization and deserialization processes, such as parsing techniques and the role of schemas. To illustrate the practical implications of choosing a serialization format, we present hypothetical performance results in the form of tables, comparing formats based on metrics like serialization deserialization speed and resulting data size. The discussion analyzes these results, highlighting the trade offs involved in selecting a text serialization format for specific use cases. This work aims to provide a comprehensive resource for understanding and applying text serialization in various computational domains.