CAIN

Publications

2024

Vladislav Indykov
Component-based Approach to Software Engineering of Machine Learning-enabled Systems. CAIN (2024)
Jati H. Husen, Jomphon Runpakprakun, Sun Chang, Hironori Washizaki, Hnin Thandar Tun, Nobukazu Yoshioka, Yoshiaki Fukazawa
Evaluation of The Generality of Multi-view Modeling Framework for ML Systems. CAIN (2024)
Ziyu Li, Donghwan Shin
Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. CAIN (2024)
Andrei Paleyes, Han-Bo Li, Neil D. Lawrence
Can causality accelerate experimentation in software systems? CAIN (2024)
Lauren Olson
Custom Developer GPT for Ethical AI Solutions. CAIN (2024)
Saeid Tizpaz-Niari, Sriram Sankaranarayanan
Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory. CAIN (2024)
Mojtaba Mostafavi Ghahfarokhi, Hamed Jahantigh, Alireza Asadi, Sepehr Kianiangolafshani, Ashkan Khademian, Abbas Heydarnoori
A Roadmap for Enriching Jupyter Notebooks Documentation with Kaggle Data. CAIN (2024)
Gilberto Recupito, Raimondo Rapacciuolo, Dario Di Nucci, Fabio Palomba
Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality. CAIN (2024)
Minh-Tri Nguyen, Hong Linh Truong, Tram Truong Huu
Novel Contract-based Runtime Explainability Framework for End-to-End Ensemble Machine Learning Serving. CAIN (2024)
Wanqin Ma, Chenyang Yang, Christian Kästner
(Why) Is My Prompt Getting Worse? Rethinking Regression Testing for Evolving LLM APIs. CAIN (2024)
Santiago del Rey
Software Design Decisions for Greener Machine Learning-based Systems. CAIN (2024)
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek
Seven Failure Points When Engineering a Retrieval Augmented Generation System. CAIN (2024)
Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
A Combinatorial Approach to Hyperparameter Optimization. CAIN (2024)
Negar Alizadeh, Fernando Castor
Green AI: a Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures. CAIN (2024)
Felix Viktor Jedrzejewski
Threat Modeling of ML-intensive Systems: Research Proposal. CAIN (2024)
Rafiullah Omar
Energy-Efficient Development of ML-Enabled Systems: A Data-Centric Approach. CAIN (2024)
Matthias Wagner
Continuous Quality Assurance and ML Pipelines under the AI Act. CAIN (2024)
Gustavo Pinto, Cleidson R. B. de Souza, Thayssa A. da Rocha, Igor Steinmacher, Alberto de Souza, Edward Monteiro
Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomes. CAIN (2024)
Jie JW Wu
An Exploratory Study of V-Model in Building ML-Enabled Software: A Systems Engineering Perspective. CAIN (2024)
Lorena Barreto Simedo Pacheco, Musfiqur Rahman, Fazle Rabbi, Pouya Fathollahzadeh, Ahmad Abdellatif, Emad Shihab, Tse-Hsun (Peter) Chen, Jinqiu Yang, Ying Zou
DVC in Open Source ML-development: The Action and the Reaction. CAIN (2024)
Francisco Durán, Silverio Martínez-Fernández, Matias Martinez, Patricia Lago
Identifying Architectural Design Decisions for Achieving Green ML Serving. CAIN (2024)
Vanilson Arruda Burégio, Iverson Pereira, Henrique Cabral
Innovating Translation: Lessons Learned from BWX Generative Language Engine. CAIN (2024)
Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI, CAIN 2024, Lisbon, Portugal, April 14-15, 2024 CAIN (2024)
Hironori Washizaki, Nobukazu Yoshioka
AI Security Continuum: Concept and Challenges. CAIN (2024)
Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz
Green Runner: A Tool for Efficient Deep Learning Component Selection. CAIN (2024)
Dawen Zhang, Boming Xia, Yue Liu, Xiwei Xu, Thong Hoang, Zhenchang Xing, Mark Staples, Qinghua Lu, Liming Zhu
Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective. CAIN (2024)
Hiroshi Tanaka, Masaru Ide, Jun Yajima, Sachiko Onodera, Kazuki Munakata, Nobukazu Yoshioka
Taxonomy of Generative AI Applications for Risk Assessment. CAIN (2024)
Gustavo Rodrigues dos Reis, Adrian Mos, Mario Cortes Cornax, Cyril Labbé
Data Selection Driven by Item Difficulty: On Investigating Data Efficient Practice for Hyperparameter Search. CAIN (2024)
Raphael Cabral, Marcos Kalinowski, Maria Teresa Baldassarre, Hugo Villamizar, Tatiana Escovedo, Hélio Lopes
Investigating the Impact of SOLID Design Principles on Machine Learning Code Understanding. CAIN (2024)
Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen
Is Your Anomaly Detector Ready for Change? Adapting AIOps Solutions to the Real World. CAIN (2024)
Qinghua Lu, Liming Zhu, Xiwei Xu, Yue Liu, Zhenchang Xing, Jon Whittle
A Taxonomy of Foundation Model based Systems through the Lens of Software Architecture. CAIN (2024)
Md Tajmilur Rahman, Rahul Singh, Mir Yousuf Sultan
Automating Patch Set Generation from Code Reviews Using Large Language Models. CAIN (2024)
Ye Yuan, Jiacheng Shi, Zongyao Zhang, Kaiwei Chen, Jingzhi Zhang, Vincenzo Stoico, Ivano Malavolta
The Impact of Knowledge Distillation on the Energy Consumption and Runtime Efficiency of NLP Models. CAIN (2024)
Keerthiga Rajenthiram
Optimizing Data Analytics Workflows through User-driven Experimentation. CAIN (2024)
Diaeddin Rimawi, Antonio Liotta, Marco Todescato, Barbara Russo
Modeling Resilience of Collaborative AI Systems. CAIN (2024)
Erik Johannes Husom, Sagar Sen, Arda Goknil
Engineering Carbon Emission-aware Machine Learning Pipelines. CAIN (2024)
Boming Xia, Qinghua Lu, Liming Zhu, Sung Une Lee, Yue Liu, Zhenchang Xing
Towards a Responsible AI Metrics Catalogue: A Collection of Metrics for AI Accountability. CAIN (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)
Maria Teresa Baldassarre, Domenico Gigante, Marcos Kalinowski, Azzurra Ragone
POLARIS: A Framework to Guide the Development of Trustworthy AI Systems. CAIN (2024)
Martin Hollender, Chaojun Xu, Ruomu Tan
Engineering Challenges in Industrial AI. CAIN (2024)
Junji Hashimoto, Nobukazu Yoshioka
A Domain Specific Language for Specification of Risk-oriented Object Detection Requirements. CAIN (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)
Krishna Ronanki, Beatriz Cabrero Daniel, Christian Berger
Prompt Smells: An Omen for Undesirable Generative AI Outputs. CAIN (2024)
Gereon Weiss, Marc Zeller, Hannes Schoenhaar, Christian Drabek, Andreas Kreutz
Approach for Argumenting Safety on Basis of an Operational Design Domain. CAIN (2024)
Mojtaba Mostafavi Ghahfarokhi, Ashkan Khademian, Sepehr Kianiangolafshani, Alireza Asadi, Hamed Jahantigh, Abbas Heydarnoori
Beyond Syntax: Unleashing the Power of Computational Notebooks Code Metrics in Documentation Generation. CAIN (2024)
Zakaria Chihani
Trustworthy AI: Industry-Guided Tooling of the Methods. CAIN (2024)
Tajkia Rahman Toma, Cor-Paul Bezemer
An Exploratory Study of Dataset and Model Management in Open Source Machine Learning Applications. CAIN (2024)
Petra Heck
What About the Data? A Mapping Study on Data Engineering for AI Systems. CAIN (2024)
Ali Nouri, Beatriz Cabrero Daniel, Fredrik Törner, Håkan Sivencrona, Christian Berger
Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models. CAIN (2024)

2023

Marc Zeller, Martin Rothfelder, Cornel Klein
safe.trAIn - Engineering and Assurance of a Driverless Regional Train. CAIN (2023)