How LLM Saved Me from Struggling with Experiment Reproduction: LEO Networking as A Case Study

Reproducing network experiments is critical to advancing the research in computer networks. However, in reality many researchers often struggle with experiment reproduction: not only because reading, understanding, and debugging prior work is time-consuming and labor-intensive, but also because not all papers publicly release their code, thereby forcing subsequent researchers to re-implement experiments from scratch.

Authors

Institutions

Publication Details

Published
2025-08-19
DOI
https://doi.org/10.1145/3748749.3749084
Primary Topic
Peer-to-Peer Network Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How LLM Saved Me from Struggling with Experiment Reproduction: LEO Networking as A Case Study

Hewu Li, Qian Wu, Zeqi Lai, Jun Liu et al.
Peer-to-Peer Network Technologies
article

How LLM Saved Me from Struggling with Experiment Reproduction: LEO Networking as A Case Study

Hewu Li, Qian Wu, Zeqi Lai, Jun Liu, Yunan Hou, Yuanjie Li, Zhifeng Han, Xin Xie, Yibo Wang
article en

Abstract

Reproducing network experiments is critical to advancing the research in computer networks. However, in reality many researchers often struggle with experiment reproduction: not only because reading, understanding, and debugging prior work is time-consuming and labor-intensive, but also because not all papers publicly release their code, thereby forcing subsequent researchers to re-implement experiments from scratch.

Tsinghua University (CN)
Openalex Percentile: Top 76%
Peer-to-Peer Network Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.