Welcome to the replication package of our paper On the Study of ML Cloud Service Misuses: An Industrial Perspective! 🚀 This repository compiles all results from the systematic review of literature, mining of GitHub repositories, and analysis of survey responses. It aims to uncover trends, patterns, and insights across multiple software development and research projects.
This repository contains the following resources:
- A collection of research papers and publications gathered during the systematic literature review: here
- A curated collection of GitHub repositories related to the research topics: ML services and antipatterns.
- These repositories were mined using Python scripts based on keywords found in the README/description of each repository.
- In-depth information on the GitHub repositories, including: descriptions, contributors, number of stars, and forks.
- This analysis identifies commonalities and misuses across the projects: here
- Responses collected from our pilot interviews.
- The data has been anonymized to protect the privacy of participants.
- Provides valuable insights into participants' feedback on the survey, including remarks on its length, consistency, and any duplicate questions: here
- Responses collected from our survey.
- The data has been anonymized to protect the privacy of participants.
- Provides valuable insights into developer perspectives on ML service misuses: here
- Data Mining: Python, GitHub API, StackOverflow API
- Data Analysis: Python, Understand tool
- Survey Platform: Google Forms
- Literature Review Tools: Google Scholar
Explore the catalog here
Thank you for visiting! 🎉