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The introduction of machine learning (ML) components in software projects has created the need for software engineers to collaborate with data scientists and other specialists. While collaboration can always be challenging, ML introduces…

Software Engineering · Computer Science 2022-02-14 Nadia Nahar , Shurui Zhou , Grace Lewis , Christian Kästner

IT systems of today are becoming larger and more complex, rendering their human supervision more difficult. Artificial Intelligence for IT Operations (AIOps) has been proposed to tackle modern IT administration challenges thanks to AI and…

Computers and Society · Computer Science 2020-12-17 Paolo Notaro , Jorge Cardoso , Michael Gerndt

Machine learning algorithms can perform well when trained on large datasets. While large organisations often have considerable data assets, it can be difficult for these assets to be unified in a manner that makes training possible. Data is…

Machine Learning · Computer Science 2022-03-25 Tiffany Tuor , Joshua Lockhart , Daniele Magazzeni

As information becomes increasingly sizable for organizations to maintain the challenge of organizing data still remains. More importantly, the on-going process of analysing incoming data occurs on a continual basis and organizations should…

Databases · Computer Science 2021-05-19 Bryar A. Hassan , Shko M. Qader

Over the past few years, ubiquitous, or pervasive computing has gained popularity as the primary approach for a wide range of applications, including enterprise-grade systems, consumer applications, and gaming systems. Ubiquitous computing…

Artificial Intelligence · Computer Science 2025-07-14 Cristian Bleotiu , Stefan Saraev , Bogdan Hobeanu , Andrei Ionut Damian

[Context] Systems incorporating Machine Learning (ML) models, often called ML-enabled systems, have become commonplace. However, empirical evidence on how ML-enabled systems are engineered in practice is still limited, especially for…

Machine Learning (ML) has emerged as a pivotal technology in the operation of large and complex systems, driving advancements in fields such as autonomous vehicles, healthcare diagnostics, and financial fraud detection. Despite its…

Cryptography and Security · Computer Science 2026-02-17 Xinrui Zhang , Pincan Zhao , Jason Jaskolka , Heng Li , Rongxing Lu

DevOps and Artificial Intelligence (AI) are interconnected with each other. DevOps is a business-driven approach to providing quickly delivered quality software, and AI is the technology that can be used in the system to enhance its…

Software Engineering · Computer Science 2022-06-02 Mamdouh Alenezi , Mohammad Zarour , Mohammad Akour

As artificial intelligence, machine learning, and data science continue to drive the data-centric economy, the challenges of implementing machine learning on a single machine due to extensive data and computational needs have led to the…

Networking and Internet Architecture · Computer Science 2024-07-31 Boyang Yan

Heterogeneous hardware and dynamic workloads worsen long-standing OS bottlenecks in scalability, adaptability, and manageability. At the same time, advances in machine learning (ML), large language models (LLMs), and agent-based methods…

Operating Systems · Computer Science 2025-11-12 Yifan Zhang , Xinkui Zhao , Ziying Li , Guanjie Cheng , Jianwei Yin , Lufei Zhang , Zuoning Chen

Companies dealing with Artificial Intelligence (AI) models in Autonomous Systems (AS) face several problems, such as users' lack of trust in adverse or unknown conditions, gaps between software engineering and AI model development, and…

Software Engineering · Computer Science 2021-04-26 Silverio Martínez-Fernández , Xavier Franch , Andreas Jedlitschka , Marc Oriol , Adam Trendowicz

Data-centric AI has shed light on the significance of data within the machine learning (ML) pipeline. Recognizing its significance, academia, industry, and government departments have suggested various NLP data research initiatives. While…

Databases · Computer Science 2023-06-27 Eujeong Choi , Chanjun Park

In the last years machine learning (ML) has moved from a academic endeavor to a pervasive technology adopted in almost every aspect of computing. ML-powered products are now embedded in our digital lives: from recommendations of what to…

Machine Learning · Computer Science 2021-07-20 Piero Molino , Christopher Ré

Hardly any other area of research has recently attracted as much attention as machine learning (ML) through the rapid advances in artificial intelligence (AI). This publication provides a short introduction to practical concepts and methods…

General Economics · Economics 2020-12-17 Ali R. Baghirzade

In an increasing number of AI scenarios, collaborations among different organizations or agents (e.g., human and robots, mobile units) are often essential to accomplish an organization-specific mission. However, to avoid leaking useful and…

Machine Learning · Computer Science 2020-12-08 Xun Xian , Xinran Wang , Jie Ding , Reza Ghanadan

Object-Oriented Programming (OOP) has become a crucial paradigm for managing the growing complexity of modern software systems, particularly in fields like machine learning, deep learning, large language models (LLM), and data analytics.…

Computation and Language · Computer Science 2025-12-24 Tianyang Wang , Ziqian Bi , Keyu Chen , Jiawei Xu , Qian Niu , Junyu Liu , Benji Peng , Ming Li , Sen Zhang , Xuanhe Pan , Jinlang Wang , Pohsun Feng , Yizhu Wen , Xinyuan Song , Ming Liu

Background. The rapid and growing popularity of machine learning (ML) applications has led to an increasing interest in MLOps, that is, the practice of continuous integration and deployment (CI/CD) of ML-enabled systems. Aims. Since changes…

Software Engineering · Computer Science 2022-09-26 Fabio Calefato , Filippo Lanubile , Luigi Quaranta

Context. Despite the increasing adoption of Machine Learning Operations (MLOps), teams still encounter challenges in effectively applying this paradigm to their specific projects. While there is a large variety of available tools usable for…

Software Engineering · Computer Science 2024-09-12 Faezeh Amou Najafabadi , Justus Bogner , Ilias Gerostathopoulos , Patricia Lago

Organizations rely on machine learning engineers (MLEs) to deploy models and maintain ML pipelines in production. Due to models' extensive reliance on fresh data, the operationalization of machine learning, or MLOps, requires MLEs to have…

Human-Computer Interaction · Computer Science 2024-03-26 Shreya Shankar , Rolando Garcia , Joseph M Hellerstein , Aditya G Parameswaran

We outline a comprehensive framework for artificial intelligence (AI) Application Operations (AIAppOps), based on real-world experiences from diverse organizations. Data-driven projects pose additional challenges to organizations due to…

Computers and Society · Computer Science 2026-01-13 Daniel Jönsson , Mattias Tiger , Stefan Ekberg , Daniel Jakobsson , Mattias Jonhede , Fredrik Viksten