CodeFuse-Query: A Data-Centric Static Code Analysis System for Large-Scale Organizations

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Bibliografiska uppgifter
I publikationen:arXiv.org (Jan 3, 2024), p. n/a
Huvudupphov: Xie, Xiaoheng
Övriga upphov: Fan, Gang, Lin, Xiaojun, Zhou, Ang, Li, Shijie, Zheng, Xunjin, Liang, Yinan, Zhang, Yu, Yu, Na, Li, Haokun, Chen, Xinyu, Chen, Yingzhuang, Yi Zhen, Dong, Dejun, Fu, Xianjin, Su, Jinzhou, Pan, Fuxiong, Luo, Pengshuai, Feng, Youzheng, Hu, Ruoxiang, Fan, Jing, Zhou, Jinguo, Xiao, Xiao, Peng, Di
Utgiven:
Cornell University Library, arXiv.org
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022 |a 2331-8422 
035 |a 2910030008 
045 0 |b d20240103 
100 1 |a Xie, Xiaoheng 
245 1 |a CodeFuse-Query: A Data-Centric Static Code Analysis System for Large-Scale Organizations 
260 |b Cornell University Library, arXiv.org  |c Jan 3, 2024 
513 |a Working Paper 
520 3 |a In the domain of large-scale software development, the demands for dynamic and multifaceted static code analysis exceed the capabilities of traditional tools. To bridge this gap, we present CodeFuse-Query, a system that redefines static code analysis through the fusion of Domain Optimized System Design and Logic Oriented Computation Design. CodeFuse-Query reimagines code analysis as a data computation task, support scanning over 10 billion lines of code daily and more than 300 different tasks. It optimizes resource utilization, prioritizes data reusability, applies incremental code extraction, and introduces tasks types specially for Code Change, underscoring its domain-optimized design. The system's logic-oriented facet employs Datalog, utilizing a unique two-tiered schema, COREF, to convert source code into data facts. Through Godel, a distinctive language, CodeFuse-Query enables formulation of complex tasks as logical expressions, harnessing Datalog's declarative prowess. This paper provides empirical evidence of CodeFuse-Query's transformative approach, demonstrating its robustness, scalability, and efficiency. We also highlight its real-world impact and diverse applications, emphasizing its potential to reshape the landscape of static code analysis in the context of large-scale software development.Furthermore, in the spirit of collaboration and advancing the field, our project is open-sourced and the repository is available for public access 
653 |a Data analysis 
653 |a Software 
653 |a Computation 
653 |a Source code 
653 |a Software development 
653 |a Static code analysis 
653 |a Queries 
653 |a Task complexity 
653 |a Systems design 
653 |a Empirical analysis 
653 |a Resource utilization 
653 |a Design optimization 
653 |a Query languages 
700 1 |a Fan, Gang 
700 1 |a Lin, Xiaojun 
700 1 |a Zhou, Ang 
700 1 |a Li, Shijie 
700 1 |a Zheng, Xunjin 
700 1 |a Liang, Yinan 
700 1 |a Zhang, Yu 
700 1 |a Yu, Na 
700 1 |a Li, Haokun 
700 1 |a Chen, Xinyu 
700 1 |a Chen, Yingzhuang 
700 1 |a Yi Zhen 
700 1 |a Dong, Dejun 
700 1 |a Fu, Xianjin 
700 1 |a Su, Jinzhou 
700 1 |a Pan, Fuxiong 
700 1 |a Luo, Pengshuai 
700 1 |a Feng, Youzheng 
700 1 |a Hu, Ruoxiang 
700 1 |a Fan, Jing 
700 1 |a Zhou, Jinguo 
700 1 |a Xiao, Xiao 
700 1 |a Peng, Di 
773 0 |t arXiv.org  |g (Jan 3, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2910030008/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2401.01571