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Self-Admitted Technical Debt (SATD) encompasses a wide array of sub-optimal design and implementation choices reported in software artefacts (e.g., code comments and commit messages) by developers themselves. Such reports have been central…

Software Engineering · Computer Science 2024-03-05 Nicolás E. Díaz Ferreyra , Mojtaba Shahin , Mansooreh Zahedi , Sodiq Quadri , Ricardo Scandariato

This is the Dagstuhl Perspectives Workshop 24452 manifesto on Reframing Technical Debt. The manifesto begins with a one-page summary of Values, Beliefs, and Principles. It then elaborates on each Value, Belief, and Principle to explain…

Software Engineering · Computer Science 2025-05-20 Paris Avgeriou , Ipek Ozkaya , Heiko Koziolek , Zadia Codabux , Neil Ernst

With the increasing complexity of industrial systems, there is a pressing need for predictive maintenance to avoid costly downtime and disastrous outcomes that could be life-threatening in certain domains. With the growing popularity of the…

Artificial Intelligence · Computer Science 2025-09-30 Leila Ismail , Abdelmoneim Abdelmoti , Arkaprabha Basu , Aymen Dia Eddine Berini , Mohammad Naouss

In this paper an analysis of a technical support data with the goal of identifying process improvement actions for reducing interrupts is presented. A technical support chat is established and used to provide internal developer support to…

Social and Information Networks · Computer Science 2015-10-19 Zádor Dániel Kelemen , Balázs Tódor , Sándor Hodosi , Ákos Somfai

Keeping track of and managing Self-Admitted Technical Debts (SATDs) are important to maintaining a healthy software project. This requires much time and effort from human experts to identify the SATDs manually. The current automated…

Software Engineering · Computer Science 2020-10-20 Zhe Yu , Fahmid Morshed Fahid , Huy Tu , Tim Menzies

Developers often leave behind clues in their code, admitting where it falls short, known as Self-Admitted Technical Debt (SATD). In the world of Scientific Software (SSW), where innovation moves fast and collaboration is key, such debt is…

Software Engineering · Computer Science 2025-11-24 Eric L. Melin , Ahmed Musa Awon , Nasir U. Eisty , Neil A. Ernst , Shurui Zhou

Temporal-Difference (TD) learning is a standard and very successful reinforcement learning approach, at the core of both algorithms that learn the value of a given policy, as well as algorithms which learn how to improve policies.…

Machine Learning · Computer Science 2020-06-17 Mingde Zhao

Complexity is an inherent attribute of any project. The purpose of defining and documenting complexity is to have an early warning tool allowing a project team to focus on certain areas and aspects of the project in order to prevent and…

Software Engineering · Computer Science 2015-12-25 Alexei Botchkarev , Patrick Finnigan

Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is…

Human-Computer Interaction · Computer Science 2021-02-23 Jip van Stijn

Software and systems traceability is essential for downstream tasks such as data-driven software analysis and intelligent tool development. However, despite the increasing attention to mining and understanding technical debt in software…

Software Engineering · Computer Science 2023-04-18 Mohammad Sadegh Sheikhaei , Yuan Tian

Individuals lack oversight over systems that process their data. This can lead to discrimination and hidden biases that are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not…

Software Engineering · Computer Science 2023-05-22 Valentin Zieglmeier , Alexander Pretschner

Instant payment infrastructures have stringent performance requirements, processing millions of transactions daily with zero-downtime expectations. Traditional monitoring approaches fail to bridge the gap between technical infrastructure…

Machine Learning · Computer Science 2025-10-28 Lorenzo Porcelli

We introduce a novel digital twin framework for predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the digital twin framework can be used to enhance automotive safety and…

Machine Learning · Computer Science 2024-08-13 Vispi Karkaria , Jie Chen , Christopher Luey , Chase Siuta , Damien Lim , Robert Radulescu , Wei Chen

Software-defined networking offers numerous benefits against the legacy networking systems through simplifying the process of network management and reducing the cost of network configuration. Currently, the management of failures in the…

Networking and Internet Architecture · Computer Science 2019-04-02 Ali Malik , Benjamin Aziz , Mo Adda , Chih-Heng Ke

Ant Credit Pay is a consumer credit service in Ant Financial Service Group. Similar to credit card, loan default is one of the major risks of this credit product. Hence, effective algorithm for default prediction is the key to losses…

Machine Learning · Computer Science 2020-04-02 Jianbin Lin , Zhiqiang Zhang , Jun Zhou , Xiaolong Li , Jingli Fang , Yanming Fang , Quan Yu , Yuan Qi

The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce, yet it is often viewed primarily through an internal individual lens. In this position paper, we propose framing the prevalence of IP as a…

Software Engineering · Computer Science 2026-02-17 Paloma Guenes , Rafael Tomaz , Maria Teresa Baldassarre , Alexander Serebrenik

In modern software engineering, build systems play the crucial role of facilitating the conversion of source code into software artifacts. Recent research has explored high-level causes of build failures, but has largely overlooked the…

Software Engineering · Computer Science 2025-04-03 Anwar Ghammam , Dhia Elhaq Rzig , Mohamed Almukhtar , Rania Khalsi , Foyzul Hassan , Marouane Kessentini

Fault detection is crucial in industrial systems to prevent failures and optimize performance by distinguishing abnormal from normal operating conditions. Data-driven methods have been gaining popularity for fault detection tasks as the…

Machine Learning · Computer Science 2024-06-12 Han Sun , Kevin Ammann , Stylianos Giannoulakis , Olga Fink

Background. Code Technical Debt (Code TD) prediction has gained significant attention in recent software engineering research. However, no standardized approach to Code TD prediction fully captures the factors influencing its evolution.…

Software Engineering · Computer Science 2025-06-23 Mikel Robredo , Nyyti Saarimaki , Matteo Esposito , Davide Taibi , Rafael Penaloza , Valentina Lenarduzzi

Self-Admitted Technical Debt (SATD) annotates development decisions that intentionally exchange long-term software artifact quality for short-term goals. Recent work explores the existence of SATD clones (duplicate or near duplicate SATD…

Software Engineering · Computer Science 2024-02-15 Tao Xiao , Zhili Zeng , Dong Wang , Hideaki Hata , Shane McIntosh , Kenichi Matsumoto