Published August 21, 2023 | Version 1.0.1
Dataset Open

Replication Package for "Compatibility Issues in Deep Learning Systems: Problems and Opportunities"

  • 1. Nanjing University of Aeronautics and Astronautics
  • 2. Southern University of Science and Technology
  • 3. University of New South Wales

Description

This dataset contains scripts and data used to generate relevant results for this paper. Detailed information and procedure to reproduce our results are described in README.md. 

code

This folder contains two Python scripts: soextractor.py is used to extract 3,072 high-quality StackOverflow (SO) posts and soextractor_tags.py is used to extract the number of posts for the tags on SO. For detailed data collection criteria, please refer to Section 3.1 of our paper.

DL compatibility issues.xlsx

This file provides all the collected 3,072 issues, in which each line indicates whether the issue is a DL compatibility issue. Among them, 352 are DL compatibility issues. We also provide information on the library, stage, symptom, type, solution, root cause, and exception type for the DL compatibility issues. For the type CORE-TPL, we also provide backward-incompatible or forward-incompatible as well as API evolution patterns. For detailed manual classification of DL compatibility issues, please refer to Section 3.2 of our paper.

Tool Survey.xlsx 

This file includes all the papers collected from the three top SE conferences (i.e., ICSE, FSE, and ASE) in recent five years (18-22). Each line of each sheet provides the following information: (a) Title, (b) Year, (c) Conference, and (d) Type. For the detailed paper collection procedure, please refer to Section 5 of our paper.

Files

FSE23Dataset.zip

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