An Exploratory Study of Machine Learning Model Stores

Several organizations have introduced stores that provide public access to pretrained machine learning models and infrastructure. We examine three of them and compare the information they provide against two mobileapp stores and among themselves.

[1]  Slinger Jansen,et al.  Defining App Stores: The Role of Curated Marketplaces in Software Ecosystems , 2013, ICSOB.

[2]  N. Jones,et al.  Top 10 Strategic Technology Trends for 2019: A Gartner Trend Insight Report , 2018 .

[3]  Lei Ma,et al.  DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems , 2018, 2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE).

[4]  Vijay Vasudevan,et al.  Learning Transferable Architectures for Scalable Image Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[5]  Foutse Khomh,et al.  The Open-Closed Principle of Modern Machine Learning Frameworks , 2018, 2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR).

[6]  Ahmed E. Hassan,et al.  Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store , 2015, Empirical Software Engineering.

[7]  Erik Meijer Behind every great deep learning framework is an even greater programming languages concept (keynote) , 2018, ESEC/SIGSOFT FSE.

[8]  Yifan Chen,et al.  An empirical study on TensorFlow program bugs , 2018, ISSTA.

[9]  Meiyappan Nagappan,et al.  Future Trends in Software Engineering Research for Mobile Apps , 2016, 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER).

[10]  Suman Jana,et al.  DeepTest: Automated Testing of Deep-Neural-Network-Driven Autonomous Cars , 2017, 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE).

[11]  Ahmed E. Hassan,et al.  What Do Mobile App Users Complain About? , 2015, IEEE Software.

[12]  Junfeng Yang,et al.  DeepXplore: Automated Whitebox Testing of Deep Learning Systems , 2017, SOSP.

[13]  Paul Ralph,et al.  Grounded Theory in Software Engineering Research: A Critical Review and Guidelines , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).

[14]  Michael I. Jordan,et al.  Ray: A Distributed Framework for Emerging AI Applications , 2017, OSDI.