PurdueDualityLab/PTM-Naming

3

stars

206

commits

Jupyter Notebook

primary language

Apr 18, 2025

updated

README

EMSE Artifact

Artifact repository for paper: “I see models being a whole other thing”: An Empirical Study of Pre-Trained Model Naming Conventions and A Tool for Enhancing Naming Consistency

Overview

  • Survey study ($5.1):
    • This part of our study was used to answer RQ1-3 in the paper.
  • Repository mining ($5.2):
    • This part of our study was used to answer RQ2, 4 in the paper.
  • DARA ($7.2):
    • This part of our study was used to answer RQ4 in the paper.

Directory Structure

Top-level folderSecond-level folder
Naming_anomaly_detection/APTM/
DARA/
data_files/
tools/
vector/
Naming_practices/naming_conventions/
naming_elements/
survey/Instruments/
data/

Survey Study ($5.1)

This folder includes scripts and data relevant to Table 1, Table 2, Table 3, Table 4, Figure 5, Table 5, Table 6, Table 7, Table 8, Table 9, Table 10 in the paper.

Repository mining ($5.2)

This folder includes scripts and data relevant to Figure 4, Figure 5, Figure 6, Table 5, and Table 6 in the paper.

  • Naming elements analysis

    • The prompts and scripts to analyze the naming elements of the PTMs.
    • The manually labeled groud truth data for evaluation.
  • Naming convention analysis

    • The prompts and scripts to analyze the naming conventions of the PTMs.
    • The manually labeled groud truth data for evaluation.

Naming_anomaly_detection ($7.2)

This folder includes scripts and data relevant to Listing 1, Listing 2, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, and Table 12, Table 13, Table 14, Table 15 in the paper.

  • APTMs
    • The APTM model and graph conversion pipeline.
  • DARA
    • The DNN Architecture Assessment pipeline.
  • Data files
    • The data collections scripts files used in the study.
    • The collected data files used in the study.
  • Tools
    • The utils used in the study.
  • Vector
    • The feature extractors used in the study.

Contributors

cwc020730

100 commits

calicio

82 commits

Wenxin-Jiang

24 commits

PurdueDualityLab/PTM-Naming

3

stars

206

commits

Jupyter Notebook

primary language

Apr 18, 2025

updated

README

EMSE Artifact

Artifact repository for paper: “I see models being a whole other thing”: An Empirical Study of Pre-Trained Model Naming Conventions and A Tool for Enhancing Naming Consistency

Overview

  • Survey study ($5.1):
    • This part of our study was used to answer RQ1-3 in the paper.
  • Repository mining ($5.2):
    • This part of our study was used to answer RQ2, 4 in the paper.
  • DARA ($7.2):
    • This part of our study was used to answer RQ4 in the paper.

Directory Structure

Top-level folderSecond-level folder
Naming_anomaly_detection/APTM/
DARA/
data_files/
tools/
vector/
Naming_practices/naming_conventions/
naming_elements/
survey/Instruments/
data/

Survey Study ($5.1)

This folder includes scripts and data relevant to Table 1, Table 2, Table 3, Table 4, Figure 5, Table 5, Table 6, Table 7, Table 8, Table 9, Table 10 in the paper.

Repository mining ($5.2)

This folder includes scripts and data relevant to Figure 4, Figure 5, Figure 6, Table 5, and Table 6 in the paper.

  • Naming elements analysis

    • The prompts and scripts to analyze the naming elements of the PTMs.
    • The manually labeled groud truth data for evaluation.
  • Naming convention analysis

    • The prompts and scripts to analyze the naming conventions of the PTMs.
    • The manually labeled groud truth data for evaluation.

Naming_anomaly_detection ($7.2)

This folder includes scripts and data relevant to Listing 1, Listing 2, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, and Table 12, Table 13, Table 14, Table 15 in the paper.

  • APTMs
    • The APTM model and graph conversion pipeline.
  • DARA
    • The DNN Architecture Assessment pipeline.
  • Data files
    • The data collections scripts files used in the study.
    • The collected data files used in the study.
  • Tools
    • The utils used in the study.
  • Vector
    • The feature extractors used in the study.

Contributors

cwc020730

100 commits

calicio

82 commits

Wenxin-Jiang

24 commits

Languages

Jupyter Notebook

81.0%

Python

19.0%