Review
Automation & Control Systems
Christian Esposito, Vincenzo Moscato, Giancarlo Sperli
Summary: Social networks are essential in our daily lives, and trust management plays a crucial role in ensuring their reliability and security. However, tackling the issue of mendacious reviews remains a challenge, and further solutions are needed.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhenchun Duan, Weihong Xu, Yuantao Chen, Lin Ding
Summary: The recommendation system is a primary tool to tackle the issue of information overload, facing challenges such as data sparsity, cold start, and scalability. The ETBRec algorithm improves prediction accuracy by considering trust differences and expert definitions, with experimental results showing better performance on some evaluation metrics.
APPLIED INTELLIGENCE
(2022)
Article
Geosciences, Multidisciplinary
Hongzhou Shen, Junpeng Shi, Yihan Zhang
Summary: The use of mobile social media platforms for EIM crowdsourcing tools can facilitate the dissemination of emergency information and attract participants effectively. The study introduced a mobile crowdsourcing tool called CrowdEIM and found through formative studies and summative evaluations that tools with simple operations, based on mobile social media platforms, are more likely to be disseminated and can provide accurate and understandable emergency information.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Computer Science, Cybernetics
Marta Larusdottir, Rosa Lanzilotti, Antonio Piccinno, Ioana Visescu, Maria Francesca Costabile
Summary: Involving users in the design process is crucial for understanding and meeting user needs, but many practitioners overlook user involvement. UCD Sprint is a cost-effective process that enhances the innovativeness of company design practices through user participation.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Psychology, Multidisciplinary
Jonas R. Vaag, Gunhild B. Saetren, Thomas H. Halvorsen, Stine D. Sorgard
Summary: This study investigates the criteria for selecting super users and how middle management and super users negotiate their roles and responsibilities during technological change implementation. The main selection criteria for super users are availability and local knowledge, technological skills, pedagogical skills, and proactiveness. The roles and responsibilities can be grouped into the categories of learning culture and individual learning.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Management
Max Mulhuijzen, Jeroen P. J. de Jong
Summary: Users can contribute to the improvement of a firm's product through online user innovation communities. The contributions of professional users have better diffusion rates in the community, especially when they have high commercial motivation or favorable network positions.
Article
Psychology, Multidisciplinary
Xsiang-Yu Ma, Cheng-Chung Cho, Rui-Hsin Kao, Leng-Chuan Chiu
Summary: The study confirmed the applicability of OTC in Chinese organizations using the OTI tool, revealing that subordinates trust superiors more and colleagues trust honest negotiation, while the respectful superior and inferior subordinate relationship and hierarchical authority influence the perception of trust.
CURRENT PSYCHOLOGY
(2022)
Review
Engineering, Industrial
Khatereh Ghasemzadeh, Guido Bortoluzzi, Zornitsa Yordanova
Summary: The purpose of this study is to systematically review and consolidate existing literature on firm-user collaboration, focusing on the strategic, organizational, and managerial dynamics. The study identifies six clusters of collaboration and organizes them based on the innovation-management process, aiming to uncover further research opportunities.
Article
Computer Science, Information Systems
Lior Zalmanson, Gal Oestreicher-Singer, Yael Ecker
Summary: Through online experiments, this study found that social cues on websites indirectly affect users' likelihood of disclosing private information, and this effect is stronger when users perceive the website as trustworthy. These findings are beneficial for managers and policy makers in safeguarding users' privacy.
Article
Management
Stefanie Gustafsson, Nicole Gillespie, Rosalind Searle, Veronica Hope Hailey, Graham Dietz
Summary: This study explores how organizational trust is preserved during times of disruption and introduces the concept of trust preservation as a distinct phenomenon. A theoretical model is developed to explain how organizational actors achieve the preservation of employees' trust. The study identifies three trust preservation practices - cognitive bridging, emotional embodying, and inclusive enacting - critical to maintaining trust in disruptive contexts.
ORGANIZATION STUDIES
(2021)
Article
Chemistry, Multidisciplinary
Minsoo Lee, Soyeon Oh
Summary: The technique proposed in this paper aims to provide smarter recommendations by analyzing the semantics of social information, and has shown promising results in providing personalized information in areas such as products, restaurants, and travel services.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Cybernetics
Xingfa Shen, Wentao Lv, Jianhui Qiu, Achhardeep Kaur, Fengjun Xiao, Feng Xia
Summary: Online dating is a thriving business that raises concerns about privacy and trust. In order to maintain the safety of users, detecting malicious users is crucial. This study proposes a trust-aware detection framework based on real dating site data, which improves detection precision and recall rate through a user trust model and a data-balancing method.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Psychology, Multidisciplinary
David Cameron, Stevienna de Saille, Emily C. Collins, Jonathan M. Aitken, Hugo Cheung, Adriel Chua, Ee Jing Loh, James Law
Summary: When robots demonstrate self-awareness and communicate their intention to rectify mistakes to users, they are perceived as more capable but less likeable compared to robots that simply apologize for errors. However, robots that apologize for mistakes are more likeable and increase users' intention to use them.
COMPUTERS IN HUMAN BEHAVIOR
(2021)
Article
Computer Science, Software Engineering
Damian A. A. Tamburri, Rick Kazman, Hamed Fahimi
Summary: Forming coherent groups or teams in an organization is vital in large-scale software engineering, particularly in agile software development where self-organization and organizational flexibility are crucial. Through mixed-methods research involving interviews, surveys, and Delphi studies of real agile teams, we investigated the existence of recurrent organizational structure patterns in agile software teams and their implications on software architecture quality. Our study of 30 agile software teams revealed that out of seven recurring organizational structure patterns, a single pattern occurred over 37% of the time. This pattern reflected young communities, disappeared in established ones, and correlated with a higher number of reported architecture smells. Additionally, we found a negative correlation between a proposed organizational measure and architecture smells. These findings can help architects design both architectures and communities that best support co-evolution, while also highlighting the impact of organizational structures in software engineering beyond software architectures.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Cybernetics
Joni Salminen, Soon-Gyo Jung, Shammur Chowdhury, Dianne Ramirez Robillos, Bernard Jansen
Summary: The research demonstrates that data-driven personas have a significant impact on changing decision makers' preconceptions about users. The study found that 81% of participants changed their perceptions of the audience after interacting with personas, and 94% maintained or improved the accuracy of their perceptions. Personas can be used to alter decision makers' preconceptions about users, improving their understanding and confidence in user data.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2021)
Article
Computer Science, Software Engineering
Damian A. A. Tamburri, Rick Kazman, Hamed Fahimi
Summary: Forming coherent groups or teams in an organization is vital in large-scale software engineering, particularly in agile software development where self-organization and organizational flexibility are crucial. Through mixed-methods research involving interviews, surveys, and Delphi studies of real agile teams, we investigated the existence of recurrent organizational structure patterns in agile software teams and their implications on software architecture quality. Our study of 30 agile software teams revealed that out of seven recurring organizational structure patterns, a single pattern occurred over 37% of the time. This pattern reflected young communities, disappeared in established ones, and correlated with a higher number of reported architecture smells. Additionally, we found a negative correlation between a proposed organizational measure and architecture smells. These findings can help architects design both architectures and communities that best support co-evolution, while also highlighting the impact of organizational structures in software engineering beyond software architectures.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Information Systems
Indika Kumara, Mohamed Hameez Ariz, Mohan Baruwal Chhetri, Majid Mohammadi, Willem-Jan Van Den Heuvel, Damian A. Tamburri
Summary: The increasing heterogeneity of VM offerings on public IaaS clouds leads to a large number of deployment options for cloud applications. However, selecting the appropriate deployment variant for required performance is difficult due to the combinatorial explosion in the deployment space. To address this, we propose FOCloud, an approach that uses feature modeling, sampling, machine learning, and Explainable AI techniques to guide the deployment configuration and predict performance.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Editorial Material
Computer Science, Software Engineering
Giovanni Quattrocchi, Damian A. Tamburri
Summary: This special issue demonstrates the maturity of infrastructure code and its plethora of off-the-shelf approaches to continuous software engineering, as seen through a scientific lens.
Article
Computer Science, Software Engineering
Stefano Dalla Palma, Chiel van Asseldonk, Gemma Catolino, Dario Di Nucci, Fabio Palomba, Damian A. Tamburri
Summary: Infrastructure-as-code (IaC) is crucial for providing and managing infrastructures through configuration files, but these files may suffer from code smells that impact quality and maintenance. This paper investigates the application of a traditional implementation code smell, Large Class or Blob Blueprint, in the context of TOSCA, and compares metrics-based and unsupervised learning-based detectors on a large dataset. The results suggest a new research direction for dealing with this problem and highlight the effectiveness of metrics-based detectors in detecting Blob Blueprints.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Article
Education, Scientific Disciplines
Roberto Verdecchia, Patricia Lago
Summary: This article provides empirical insights on the hybrid teaching of software engineering courses by using a mixed-method research approach. The findings show that students prefer attending courses online for the flexibility and convenience it offers, although this comes at the cost of lower focus and interaction quality. Additionally, the research presents eight evidence-based guidelines for improving the experience of students in hybrid teaching.
IEEE TRANSACTIONS ON EDUCATION
(2023)
Article
Computer Science, Software Engineering
Istvan David, Kousar Aslam, Ivano Malavolta, Patricia Lago
Summary: This study investigates the practices and needs of collaborative Model-Driven Software Engineering (MDSE) through a mixed-method survey. The results reveal a gap between academic research and industry needs, and provide directions for further research and development of supporting techniques for collaborative MDSE.
JOURNAL OF SYSTEMS AND SOFTWARE
(2023)
Article
Computer Science, Artificial Intelligence
Majid Mohammadi, Amir Ahooye Atashin, Damian A. Tamburri
Summary: This paper proposes a simple projection neural network for '1-regularized logistic regression. Unlike other available solvers, the proposed network does not require any extra auxiliary variable or smooth approximation, and its complexity is almost the same as that of gradient descent for logistic regression without '1 regularization, thanks to the projection operator. The paper also demonstrates the convergence of the proposed neural network using Lyapunov theory and shows its superior performance in terms of execution time compared to state-of-the-art methods, while remaining competitive in accuracy and AUROC.
Article
Computer Science, Software Engineering
Giovanni Quattrocchi, Damian Andrew Tamburri, Willem-Jan Van Den Heuvel
Summary: Service continuity requires establishing a visible and understandable connection between customer experience and service operations. Manual methods for establishing this connection, such as service incident management, are time-consuming, inefficient, and prone to errors. On the other hand, artificial intelligence (AI) is emerging as an automated solution for handling the discontinuities in critical business tasks. This article introduces AI-driven incident management and proposes ACQUA, an AI approach for automatically assessing the quality of ticket descriptions, leading to improved resolution times and service continuity.
SOFTWARE-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Damian A. Tamburri, Vincent R. van Mierlo, Willem-Jan van den Heuvel
Summary: The amount of data is increasing rapidly, but its consumption is not keeping up. DataOps is a new family of techniques and tools that utilize complex cloud systems orchestration techniques to continuously harness the potential of data. This paper presents a proof-of-concept implementation of a DataOps pipeline for mitigating the effects of droughts in high-risk areas. The study focuses on a game reserve in the Waterberg area of Limpopo province, South Africa. The objectives of the paper include developing and studying a proof of concept for DataOps, exploring the applicability of individual software components in a large-scale continuous pipeline, and discussing the spatial classification of these components in a new Drought Early-Warning System (DEWS). The findings suggest that a combined model of local, regional, and global data performs the best within an acceptable timeframe for stakeholders.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Management
Majid Mohammadi, Damian A. Tamburri, Jafar Rezaei
Summary: This article examines three common fallacies in group multi-criteria decision-making and proposes solutions based on compositional data analysis to prevent misapplication of statistical operations.
GROUP DECISION AND NEGOTIATION
(2023)
Article
Computer Science, Software Engineering
Lulai Zhu, Damian Andrew Tamburri, Giuliano Casale
Summary: This paper proposes a semi-automatic approach called RADF to migrate monolithic applications to serverless architecture by decomposing them into serverless functions based on business logic analysis. The approach adopts a two-stage refactoring strategy and can generate solutions at either microservice or function level. Evaluation experiments show that RADF achieves lower coupling and relatively balanced cohesion compared to previous approaches.
SOFTWARE-PRACTICE & EXPERIENCE
(2023)
Proceedings Paper
Computer Science, Software Engineering
Indika Kumara, Fabiano Pecorelli, Gemma Catolino, Rick Kazman, Damian Andrew Tamburri, Willem-Jan van den Heuvel
Summary: MLOps refers to a set of practices and tools that automate and combine model development and model operation, enabling organizations to successfully deploy and manage their ML models in production.
2023 IEEE 20TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION, ICSA-C
(2023)
Proceedings Paper
Computer Science, Software Engineering
Luciano Baresi, Giovanni Quattrocchi, Damian A. Tamburri
2023 IEEE 20TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION, ICSA-C
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Daniel De Pascale, Giuseppe Cascavilla, Damian A. Tamburri, Willem-Jan Van den Heuvel
Summary: In recent years, there has been a rapid increase in illegal online market services on the Dark Web, allowing for easy acquisition of illicit goods through simple service interactions. To understand this emerging illegal services economy, a monitoring tool called SENSEI (Scraper for Enhanced analysis to Evaluate Illicit trends) was developed. SENSEI extracts specific service transaction trends and analyzes human behaviors behind them in order to provide insights on customers and vendors in the Dark Web. Additionally, it offers a trend analysis tool to identify and categorize relationships among different criminal activities, supporting investigation and law enforcement efforts in detecting criminal operations.
SERVICE-ORIENTED COMPUTING - ICSOC 2022 WORKSHOPS
(2023)
Article
Computer Science, Software Engineering
Stefano Lambiase, Gemma Catolino, Fabiano Pecorelli, Damian A. Tamburri, Fabio Palomba, Willem-Jan van den Heuvel, Filomena Ferrucci
Summary: This paper contributes to the existing body of knowledge on factors affecting productivity in software development by studying the cultural and geographical dispersion of a development community. The results show that cultural and geographical dispersion significantly impact productivity, suggesting that managers and practitioners should consider these aspects throughout the software development lifecycle.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
