Summary of Fullstack Bench: Evaluating Llms As Full Stack Coders, by Bytedance-seed-foundation-code-team: Yao Cheng et al.

FullStack Bench: Evaluating LLMs as Full Stack Coders

by Bytedance-Seed-Foundation-Code-Team, Yao Cheng, Jianfeng Chen, Jie Chen, Li Chen, Liyu Chen, Wentao Chen, Zhengyu Chen, Shijie Geng, Aoyan Li, Bo Li, Bowen Li, Linyi Li, Boyi Liu, Jerry Liu, Kaibo Liu, Qi Liu, Shukai Liu, Siyao Liu, Tianyi Liu, Tingkai Liu, Yongfei Liu, Rui Long, Jing Mai, Guanghan Ning, Z.Y. Peng, Kai Shen, Jiahao Su, Jing Su, Tao Sun, Yifan Sun, Yunzhe Tao, Guoyin Wang, Siwei Wang, Xuwu Wang, Yite Wang, Zihan Wang, Jinxiang Xia, Liang Xiang, Xia Xiao, Yongsheng Xiao, Chenguang Xi, Shulin Xin, Jingjing Xu, Shikun Xu, Hongxia Yang, Jack Yang, Yingxiang Yang, Jianbo Yuan, Jun Zhang, Yufeng Zhang, Yuyu Zhang, Shen Zheng, He Zhu, Ming Zhu

First submitted to arxiv on: 30 Nov 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary As capabilities of code large language models (LLMs) expand, their applications across diverse domains increase rapidly. However, most datasets only evaluate limited domains. To address this gap, we developed a comprehensive dataset, FullStack Bench, focusing on full-stack programming, encompassing various application domains like basic programming, data analysis, software engineering, mathematics, and machine learning. Additionally, we designed real-world instructions and unit test cases from 16 widely-used languages to reflect usage scenarios rather than simple translations, assessing multilingual programming capabilities. We also released an effective code execution tool (SandboxFusion) supporting various languages and packages to evaluate FullStack Bench efficiently. Our comprehensive results demonstrate the necessity and effectiveness of our dataset and tool.
Low	GrooveSquid.com (original content)	Low Difficulty Summary This paper is about a new way to test how well computer programs work together. It’s like having a special toolbox that helps us see if different programming languages can work together smoothly, just like people can speak many languages but still communicate effectively. This matters because as computers get smarter, they need to be able to understand and use lots of different languages too. The researchers created a special dataset (called FullStack Bench) with examples and tests for 16 popular programming languages. They also made a tool called SandboxFusion that helps them test these programs efficiently. The results show that this approach is useful and important.