Cover Image

Data Requirement Goal Modeling for Machine Learning Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yamani, Asma, AlAmoudi, Nadeen, Albilali, Salma, Baslyman, Malak, Hassine, Jameleddine
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging LLMs for User Stories in AI Systems: UStAI Dataset
by: Yamani, Asma, et al.
Published: (2025)

Are We Aligned? A Preliminary Investigation of the Alignment of Responsible AI Values between LLMs and Human Judgment
by: Yamani, Asma, et al.
Published: (2025)

An ML-based Approach to Predicting Software Change Dependencies: Insights from an Empirical Study on OpenStack
by: Arabat, Ali, et al.
Published: (2025)

TraceLLM: Leveraging Large Language Models with Prompt Engineering for Enhanced Requirements Traceability
by: Alturayeif, Nouf, et al.
Published: (2026)

Verifying Machine Learning Interpretability Requirements through Provenance
by: Vonderhaar, Lynn, et al.
Published: (2026)

Machine Learning with Requirements: a Manifesto
by: Giunchiglia, Eleonora, et al.
Published: (2023)

Text-to-Image Representativity Fairness Evaluation Framework
by: Yamani, Asma, et al.
Published: (2024)

Data Virtualization for Machine Learning
by: Khan, Saiful, et al.
Published: (2025)

Automating the Training and Deployment of Models in MLOps by Integrating Systems with Machine Learning
by: Liang, Penghao, et al.
Published: (2024)

Machine Learning Systems are Bloated and Vulnerable
by: Zhang, Huaifeng, et al.
Published: (2022)

Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review
by: Shivashankar, Karthik, et al.
Published: (2025)

Establishing Heuristics for Improving the Usability of GUI Machine Learning Tools for Novice Users
by: Yamani, Asma, et al.
Published: (2024)

Understanding Practitioners Perspectives on Monitoring Machine Learning Systems
by: Naveed, Hira, et al.
Published: (2025)

Monitoring Machine Learning Systems: A Multivocal Literature Review
by: Naveed, Hira, et al.
Published: (2025)

Deep Learning and Machine Learning: Advancing Big Data Analytics and Management with Design Patterns
by: Chen, Keyu, et al.
Published: (2024)

Towards MLOps: A DevOps Tools Recommender System for Machine Learning System
by: Shah, Pir Sami Ullah, et al.
Published: (2024)

How do Machine Learning Models Change?
by: Castaño, Joel, et al.
Published: (2024)

An Effective Software Risk Prediction Management Analysis of Data Using Machine Learning and Data Mining Method
by: Xu, Jinxin, et al.
Published: (2024)

The State of Documentation Practices of Third-party Machine Learning Models and Datasets
by: Oreamuno, Ernesto Lang, et al.
Published: (2023)

Spiral Model Technique For Data Science & Machine Learning Lifecycle
by: Mahadevan, Rohith
Published: (2025)

Machine Learning Systems: A Survey from a Data-Oriented Perspective
by: Cabrera, Christian, et al.
Published: (2023)

Bug Severity Prediction in Software Projects Using Supervised Machine Learning Models
by: Nice, Nafisha Tamanna
Published: (2026)

Using Small Language Models to Reverse-Engineer Machine Learning Pipelines Structures
by: Lacroix, Nicolas, et al.
Published: (2026)

Geospatial Machine Learning Libraries
by: Stewart, Adam J., et al.
Published: (2025)

Reinforcement Learning for Testing Interdependent Requirements in Autonomous Vehicles: An Empirical Study
by: Wu, Jiahui, et al.
Published: (2025)

Data vs. Model Machine Learning Fairness Testing: An Empirical Study
by: Shome, Arumoy, et al.
Published: (2024)

Requirement falsification for cyber-physical systems using generative models
by: Peltomäki, Jarkko, et al.
Published: (2023)

Can I Solve It? Identifying APIs Required to Complete OSS Task
by: Santos, Fabio, et al.
Published: (2021)

Analysing Python Machine Learning Notebooks with Moose
by: Mignard, Marius, et al.
Published: (2025)

Optimising for Energy Efficiency and Performance in Machine Learning
by: Ferreira, Emile Dos Santos, et al.
Published: (2026)

Automated Trustworthiness Testing for Machine Learning Classifiers
by: Cho, Steven, et al.
Published: (2024)

Machine Learning Operations: A Mapping Study
by: Chakraborty, Abhijit, et al.
Published: (2024)

An Empirical Analysis of Machine Learning Model and Dataset Documentation, Supply Chain, and Licensing Challenges on Hugging Face
by: Stalnaker, Trevor, et al.
Published: (2025)

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems
by: Yamani, Asma, et al.
Published: (2025)

Applications and Challenges of Fairness APIs in Machine Learning Software
by: Das, Ajoy, et al.
Published: (2025)

Continuous Management of Machine Learning-Based Application Behavior
by: Anisetti, Marco, et al.
Published: (2023)

Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility
by: Jin, Bihui, et al.
Published: (2026)

JetTrain: IDE-Native Machine Learning Experiments
by: Trofimov, Artem, et al.
Published: (2024)

Quality Issues in Machine Learning Software Systems
by: Côté, Pierre-Olivier, et al.
Published: (2023)

Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment
by: Ahmed, Shibbir, et al.
Published: (2024)