ShellFusion: Answer Generation for Shell Programming Tasks via Knowledge Fusion
Neng Zhang, Chao Liu, Xin Xia, Christoph Treude, Ying Zou, David Lo, Zibin Zheng
摘要
Shell commands are widely used for accomplishing tasks, such as network management and file manipulation, in Unix and Linux platforms. There are a large number of shell commands available. For example, 50,000+ commands are documented in the Ubuntu Manual Pages (MPs). Quite often, programmers feel frustrated when searching and orchestrating appropriate shell commands to accomplish specific tasks. To address the challenge, the shell programming community calls for easy-to-use tutorials for shell commands. However, existing tutorials (e.g., TLDR) only cover a limited number of frequently used commands for shell beginners and provide limited support for users to search for commands by a task. We propose an approach, i.e., ShellFusion, to automatically generate comprehensive answers (including relevant shell commands, scripts, and explanations) for shell programming tasks. Our approach integrates knowledge mined from Q&A posts in Stack Exchange, Ubuntu MPs, and TLDR tutorials. For a query that describes a shell programming task, ShellFusion recommends a list of relevant shell commands. Specifically, ShellFusion retrieves the top-n Q&A posts with questions similar to the query and detects shell commands with options (e.g., ls -t) from the accepted answers of the retrieved posts. Next, ShellFusion filters out irrelevant commands with descriptions in MP and TLDR that share little semantics with the query, and further ranks the candidate commands based on their similarities with the query and the retrieved posts. To help users understand how to achieve the task using a recommended command, ShellFusion generates a comprehensive answer for each command by synthesizing knowledge from Q&A posts, MPs, and TLDR. Our evaluation of 434 shell programming tasks shows that ShellFusion significantly outperforms Magnum (the stateof-the-art natural language-to-Bash command approach) by at least
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
相关 Paper
- Ahead-of-Time Analysis of Shell Program EffectsLukas Lazarek, Evangelos Lamprou, George Kapetanakis, Anirudh Narsipur 等SOSP 2026
- RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command ExplainerJiangyi Deng, Xinfeng Li, Yanjiao Chen, Yijie Bai 等NDSS 2025
- The Koala Benchmarks for the Shell: Characterization and ImplicationsEvangelos Lamprou, Ethan Williams, Georgios Kaoukis, Zhuoxuan Zhang 等USENIX ATC 2025 · 被引用 12 次
- DiSh: Dynamic Shell-Script DistributionTammam Mustafa, Konstantinos Kallas, Pratyush Das, Nikos VasilakisNSDI 2023 · 被引用 11 次
- Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow PostsWenhua Yang, Chong Zhang, Minxue PanFSE 2023 · 被引用 5 次
