activity
20182026
most citedMachine Learning for Software Engineering: A Tertiary Study

42 citations · 106 across the 23 of their papers we have counts for

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Showing 2026 · cs.SEShow all

7 papers · 2 filters

cs.SE2026

Characterizing Feedback Statements in Machine Learning Jupyter Notebooks

Arumoy Shome, Lu\is Cruz, Diomidis Spinellis +1

Machine learning development in Jupyter notebooks is iterative and feedback-driven. Practitioners author statements that reveal information about program execution and use it to de…

cs.SE2026

"It Comes in Notebooks": Changes and Challenges when Operationalizing ML Prototypes

Arumoy Shome, Luís Cruz, Diomidis Spinellis +1

Machine learning practitioners commonly prototype models in computational notebooks before transitioning them to automated production systems. Despite its prevalence, the concrete…

cs.SE2026

Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review

Dimitris Mitropoulos, Nikolaos Alexopoulos, Georgios Alexopoulos +1

Automated Code Review (ACR) systems integrating Large Language Models (LLMs) are increasingly adopted in software development workflows, ranging from interactive assistants to auto…

cs.SE2026★ 1 cited

Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment

Eileen Kapel, Jan Lennartz, Luis Cruz +2

Effective IT change management is important for businesses that depend on software and services, particularly in highly regulated sectors such as finance, where operational reliabi…

cs.SE2026

Awakening: Modern Challenges and Opportunities of Software Engineering Research

Diomidis Spinellis, Zoe Kotti

Software engineering research benefited for decades from openly available tools, accessible systems, and problems that could be studied at modest scale. Today, many of the most rel…

cs.SE2026

Bridging Behavioral Biometrics and Source Code Stylometry: A Survey of Programmer Attribution

Marek Horvath, Emilia Pietrikova, Diomidis Spinellis

Programmer attribution seeks to identify or verify the author of a source code artifact using stylistic, structural, or behavioural characteristics. This problem has been studied a…