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ZENODO
Software . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
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Artifact for Formalizing Linear Motion G-code for Invariant Checking and Differential Testing of Fabrication Tools

Source Code and Experimental Setup
Authors: He, Yumeng; Nandi, Chandrakana; Pai, Sreepathi;

Artifact for Formalizing Linear Motion G-code for Invariant Checking and Differential Testing of Fabrication Tools

Abstract

This artifact accompanies our paper Yumeng He, Chandrakana Nandi, Sreepathi Pai, "Formalizing Linear Motion G-code for Invariant Checking and Differential Testing of Fabrication Tools", submitted to OOPSLA. The paper describes an algorithm for comparing 3D printer G-code files using a novel graphical semantics and comparison algorithm. It contains: Results from our experiments that are used in the paper: from rotation invariant checking experiments, including results from error-free models from mesh repair tools experiments from slicer comparison experiments A Python implementation of our algorithms and some external dependencies Inputs and scripts to re-run our experiments STL Models to use for reproducing our experiments fully This artifact was tested on Linux and requires machines with large amount of RAM (our machine had 48GB + 32 GB swap) to rerun our experiments. It requires about 200GB of disk space uncompressed, more if you want to re-run the experiments fully. Python 3.9 or higher is required. The artifact installs into a virtual environment. This artifact is divided into three parts: Source Code and Experimental Setup (this part) Results of the Invariant Checking Experiments Results of the Slicer Comparison and Mesh Repair Tools Experiment Updates July 11, 2025: This artifact does not work with Python 3.13, failing to install open3d with a version conflict, stemming from numpy 1.26 not supporting Python 3.13. We recommend using Python 3.9, 3.10, or 3.11.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average