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20192026
most citedUnderstanding Flaky Tests: The Developer's Perspective

169 citations · 335 across the 56 of their papers we have counts for

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16 papers · 1 filter

cs.SE2026

Fairness Hazard Analysis for Socio-Technical Processes: A Multiple-Case Study in Bias-sensitive Organisational Settings

Giovanna Broccia, Lucio Lelii, Roberto Cirillo +5

Fairness is increasingly recognised as a first-class requirement in socio-technical processes, where interactions among human actors, software systems, and AI technologies may lead…

cs.SE2026

TARS: A Theory-of-Mind Agent for Personalized In-IDE Code Comprehension

Leopoldo Todisco, Antonio Della Porta, Stefano Lambiase +1

Code comprehension is one of the most time-consuming tasks in software engineering, yet most LLM-based assistants produce explanations that ignore who is asking and force developer…

cs.CR2026

The Language of Security: How Prompt Syntax Shapes Secure Code Generation in Open LLMs

Matteo Cicalese, Antonio Della Porta, Stefano Lambiase +4

Large Language Models (LLMs) are increasingly used for source code generation despite their outputs often exhibiting security vulnerabilities. Prior work shows that prompt engineer…

cs.SE2026

How Do Developers Maintain and Evolve Their Agents' Instructions? An Empirical Study

Gianmario Voria, Alfonso Cannavale, Andrea De Lucia +3

Context. Autonomous coding agents are increasingly used in software development, shifting parts of the engineering process to AI assistance. While this automation brings clear bene…

cs.SE2026

An Empirical Study of Gemini 3 for Detecting Natural Language Test Smells in Manual Test Cases

Keila Lucas, Rohit Gheyi, Márcio Ribeiro +3

Manual testing, in which testers follow natural language instructions to validate system behavior, remains essential for uncovering issues that are difficult to capture with automa…

cs.SE2026

LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda

Victoria Gomes, Delaney Selb, Fabio Palomba +2

Context: Empirical Software Engineering (ESE) faces increasing challenges due to data scale, methodological complexity, and reproducibility concerns. Large Language Models (LLMs) h…

cs.CV2026

From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models

Pir Bakhsh Khokhar, Carmine Gravino, Fabio Palomba +2

The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers cannot be easily interpreted in t…

cs.SE2026

Bias Ahead: Sensitive Prompts as Early Warnings for Fairness in Large Language Models

Gianmario Voria, Martina De Lucia, Alessandra Raia +3

Large Language Models (LLMs) are being increasingly integrated into software systems, offering powerful capabilities but also raising concerns about fairness. Existing fairness ben…

cs.SE2026

SCOPE: A Dataset of Stereotyped Prompts for Counterfactual Fairness Assessment of LLMs

Alessandra Parziale, Gianmario Voria, Valeria Pontillo +3

Large Language Models (LLMs) now serve as the foundation for a wide range of applications, from conversational assistants to decision support tools, making the issue of fairness in…

cs.SE2026

Investigating Technical Debt Types, Issues, and Solutions in Serverless Computing

Hasini Sumalee Perera, Zadia Codabux, Fabio Palomba

Serverless computing is a cloud execution model where developers run code, and the server management is handled by the cloud provider. Serverless computing is increasingly gaining…

cs.SE2026

Green Architectural Tactics in ML-enabled Systems: An LLM-based Repository Mining Study

Vincenzo De Martino, Silverio Martínez-Fernández, Fabio Palomba

Context: The increasing adoption of machine learning (ML) and artificial intelligence (AI) technologies raises growing concerns about their environmental sustainability. Developing…

cs.SE2026

Socio-Technical Well-Being of Quantum Software Communities: An Overview on Community Smells

Stefano Lambiase, Manuel De Stefano, Fabio Palomba +2

Quantum computing has gained significant attention due to its potential to solve computational problems beyond the capabilities of classical computers. With major corporations and…

cs.SE2026

Tracing Stereotypes in Pre-trained Transformers: From Biased Neurons to Fairer Models

Gianmario Voria, Moses Openja, Foutse Khomh +2

The advent of transformer-based language models has reshaped how AI systems process and generate text. In software engineering (SE), these models now support diverse activities, ac…

cs.LG2026

Transformer-Based Multi-Modal Temporal Embeddings for Explainable Metabolic Phenotyping in Type 1 Diabetes

Pir Bakhsh Khokhar, Carmine Gravino, Fabio Palomba +2

Type 1 diabetes (T1D) is a highly metabolically heterogeneous disease that cannot be adequately characterized by conventional biomarkers such as glycated hemoglobin (HbA1c). This s…

cs.SE2026

Once Upon a Team: Investigating Bias in LLM-Driven Software Team Composition and Task Allocation

Alessandra Parziale, Gianmario Voria, Valeria Pontillo +4

LLMs are increasingly used to boost productivity and support software engineering tasks. However, when applied to socially sensitive decisions such as team composition and task all…

cs.SE2026

A Defect is Being Born: How Close Are We? A Time Sensitive Forecasting Approach

Mikel Robredo, Matteo Esposito, Fabio Palomba +2

Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most a…