22 citations · 24 across the 5 of their papers we have counts for
6 papers
Threshy: Supporting Safe Usage of Intelligent Web Services
Alex Cummaudo, Scott Barnett, Rajesh Vasa +1
Increased popularity of `intelligent' web services provides end-users with machine-learnt functionality at little effort to developers. However, these services require a decision t…
A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects
Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana +2
Background: Meeting the growing industry demand for Data Science requires cross-disciplinary teams that can translate machine learning research into production-ready code. Software…
Beware the evolving 'intelligent' web service! An integration architecture tactic to guard AI-first components
Alex Cummaudo, Scott Barnett, Rajesh Vasa +2
Intelligent services provide the power of AI to developers via simple RESTful API endpoints, abstracting away many complexities of machine learning. However, most of these intellig…
Ranking Computer Vision Service Issues using Emotion
Maheswaree K Curumsing, Alex Cummaudo, Ulrike Maria Graetsch +2
Software developers are increasingly using machine learning APIs to implement 'intelligent' features. Studies show that incorporating machine learning into an application increases…
Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow
Alex Cummaudo, Rajesh Vasa, Scott Barnett +2
Intelligent services are becoming increasingly more pervasive; application developers want to leverage the latest advances in areas such as computer vision to provide new services…
Data Provenance for Sport
Andrew J. Simmons, Scott Barnett, Simon Vajda +1
Data analysts often discover irregularities in their underlying dataset, which need to be traced back to the original source and corrected. Standards for representing data provenan…