Scott Barnett

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 40

Top Topics

Mobile Applications

Top Venues

ESEC/SIGSOFT FSE

Publications

Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek
Seven Failure Points When Engineering a Retrieval Augmented Generation System. CoRR (2024)
Zafaryab Rasool, Stefanus Kurniawan, Sherwin Balugo, Scott Barnett, Rajesh Vasa, Courtney Chesser, Benjamin M. Hampstead, Sylvie Belleville, Kon Mouzakis, Alex Bahar-Fuchs
Evaluating LLMs on document-based QA: Exact answer selection and numerical extraction using CogTale dataset. Nat. Lang. Process. J. 8 (2024)
Hala Abdelkader, Mohamed Abdelrazek, Scott Barnett, Jean-Guy Schneider, Priya Rani, Rajesh Vasa
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems - A Case Study. CAIN (2024)
Shangeetha Sivasothy, Scott Barnett, Rena Logothetis, Mohamed Abdelrazek, Zafaryab Rasool, Srikanth Thudumu, Zach Brannelly
Large language models for generating rules, yay or nay? CoRR (2024)
Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz
Green Runner: A Tool for Efficient Deep Learning Component Selection. CAIN (2024)
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek
Seven Failure Points When Engineering a Retrieval Augmented Generation System. CAIN (2024)
Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Almorsy Abdelrazek
LLMs for Test Input Generation for Semantic Caches. CoRR (2024)
Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Abdelrazek
LLMs for Test Input Generation for Semantic Applications. CAIN (2024)
Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa
Comparative analysis of real issues in open-source machine learning projects. Empir. Softw. Eng. 29 (3) (2024)
Hala Abdelkader, Mohamed Abdelrazek, Scott Barnett, Jean-Guy Schneider, Priya Rani, Rajesh Vasa
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study. CoRR (2024)
Scott Barnett, Zach Brannelly, Stefanus Kurniawan, Sheng Wong
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models. CoRR (2024)
Tamal Mondal, Scott Barnett, Akash Lal, Jyothi Vedurada
Cell2Doc: ML Pipeline for Generating Documentation in Computational Notebooks. ASE (2023)
Ben Philip, Mohamed Almorsy Abdelrazek, Scott Barnett, Alessio Bonti, John Grundy
Toward a Unified mHealth Platform: A Survey of Current User Challenges and Expectations. IEEE Access 11 (2023)
Ben Philip, Yasmeen Anjeer Alshehhi, Mohamed Abdelrazek, Scott Barnett, Alessio Bonti, John Grundy
mHealthSwarm: A Unified Platform for mHealth Applications. ENASE (2023)
Hung Du, Srikanth Thudumu, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa, Kon Mouzakis
Decentralized Federated Learning Strategy with Image Classification using ResNet Architecture. CCNC (2023)
Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett
Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique. Sensors 23 (20) (2023)
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
MLGuard: Defend Your Machine Learning Model! SE4SafeML@SIGSOFT FSE (2023)
Zafaryab Rasool, Scott Barnett, Stefanus Kurniawan, Sherwin Balugo, Rajesh Vasa, Courtney Chesser, Alex Bahar-Fuchs
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset. CoRR (2023)
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
MLGuard: Defend Your Machine Learning Model! CoRR (2023)
Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz
Green Runner: A tool for efficient model selection from model repositories. CoRR (2023)
Ben Philip, Mohamed Abdelrazek, Scott Barnett, Alessio Bonti, John C. Grundy
Towards Better mHealth Apps: Understanding Current Challenges and User Expectations. MOBILESoft (2022)
Johnahan Van Zyl, Hung Du, Srikanth Thudumu, Irini Logothetis, Scott Barnett, Rajesh Vasa, Kon Mouzakis
Subspace based Anomaly Detection Framework for Point Clouds. e-Science (2022)
Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa
Comparative analysis of real bugs in open-source Machine Learning projects - A Registered Report. CoRR (2022)
Jai Kannan, Scott Barnett, Luís Cruz, Anj Simmons, Akash Agarwal
MLSmellHound: A Context-Aware Code Analysis Tool. CoRR (2022)
Irini Logothetis, Scott Barnett, Leonard Hoon, Srikanth Thudumu, Joseph Mathew, Carl Luckhoff, Gerard O'Reilly, David Collard, Rajesh Vasa, Kon Mouzakis, Mark Fitzgerald
PiMS: A Pre-ML Labelling Tool. e-Science (2022)
Jai Kannan, Scott Barnett, Luis Cruz, Anj Simmons, Akash Agarwal
MLSmellHound: A Context-Aware Code Analysis Tool. ICSE (NIER) (2022)
Hung Du, Srikanth Thudumu, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa, Kon Mouzakis
A Framework for Evaluating MRC Approaches with Unanswerable Questions. e-Science (2022)
Shangeetha Sivasothy, Scott Barnett, Niroshinie Fernando, Rajesh Vasa, Roopak Sinha, Andrew J. Simmons
Towards a taxonomy for annotation of data science experiment repositories. SCAM (2021)
Alex Cummaudo, Ulrike Maria Graetsch, Maheswaree Kissoon Curumsing, Rajesh Vasa, Scott Barnett, John Grundy
Emotions in Computer Vision Service Q&A. SEmotion@ICSE (2021)
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy, Mohamed Abdelrazek
Beware the evolving 'intelligent' web service! An integration architecture tactic to guard AI-first components. CoRR (2020)
Alex Cummaudo, Rajesh Vasa, Scott Barnett, John C. Grundy, Mohamed Abdelrazek
Interpreting cloud computer vision pain-points: a mining study of stack overflow. ICSE (2020)
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy
Threshy: supporting safe usage of intelligent web services. ESEC/SIGSOFT FSE (2020)
Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana, Akshat Bajaj, Rajesh Vasa
A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects. ESEM (2020)
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy, Mohamed Abdelrazek
Beware the evolving 'intelligent' web service! an integration architecture tactic to guard AI-first components. ESEC/SIGSOFT FSE (2020)
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy
Threshy: Supporting Safe Usage of Intelligent Web Services. CoRR (2020)
Maheswaree Kissoon Curumsing, Alex Cummaudo, Ulrike Maria Graetsch, Scott Barnett, Rajesh Vasa
Ranking Computer Vision Service Issues using Emotion. CoRR (2020)
Alex Cummaudo, Rajesh Vasa, Scott Barnett, John C. Grundy, Mohamed Abdelrazek
Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow. CoRR (2020)
Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana, Akshat Bajaj, Rajesh Vasa
A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects. CoRR (2020)
Scott Barnett, Iman Avazpour, Rajesh Vasa, John Grundy
Supporting multi-view development for mobile applications. J. Comput. Lang. 51 (2019)
Andrew J. Simmons, Scott Barnett, Simon Vajda, Rajesh Vasa
Data Provenance for Sport. CoRR (2018)
Scott Barnett, Rajesh Vasa, Antony Tang
A Conceptual Model for Architecting Mobile Applications. WICSA (2015)
Scott Barnett, Iman Avazpour, Rajesh Vasa, John C. Grundy
A multi-view framework for generating mobile apps. VL/HCC (2015)
Scott Barnett, Rajesh Vasa, John Grundy
Bootstrapping Mobile App Development. ICSE (2) (2015)