activity
20202026
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Showing 2025Show all

7 papers · 1 filter

cs.SE2025

Task-Aware Reduction for Scalable LLM-Database Systems

Marcus Emmanuel Barnes, Taher A. Ghaleb, Safwat Hassan

Large Language Models (LLMs) are increasingly applied to data-intensive workflows, from database querying to developer observability. Yet the effectiveness of these systems is cons…

cs.SE2025

From First Use to Final Commit: Studying the Evolution of Multi-CI Service Adoption

Nitika Chopra, Taher A. Ghaleb

Continuous Integration (CI) services, such as GitHub Actions and Travis CI, are widely adopted in open-source development to automate testing and deployment. Though existing resear…

cs.SE2025

Can LLMs Write CI? A Study on Automatic Generation of GitHub Actions Configurations

Taher A. Ghaleb, Dulina Rathnayake

Continuous Integration (CI) services, such as GitHub Actions, require developers to write YAML-based configurations, which can be tedious and error-prone. Despite the increasing us…

cs.SE2025

CIgrate: Automating CI Service Migration with Large Language Models

Md Nazmul Hossain, Taher A. Ghaleb

Continuous Integration (CI) configurations often need to be migrated between services (e.g., Travis CI to GitHub Actions) as projects evolve due to changes in service capabilities,…

cs.SE2025

An Empirical Study of Complexity, Heterogeneity, and Compliance of GitHub Actions Workflows

Edward Abrokwah, Taher A. Ghaleb

Continuous Integration (CI) has become a core practice in modern software engineering, enabling rapid and collaborative software delivery. GitHub Actions (GHA) has become a leading…

cs.SE2025

Security Debt in Practice: Nuanced Insights from Practitioners

Chaima Boufaied, Taher Ghaleb, Zainab Masood

With the increasing reliance on software and automation nowadays, tight deadlines, limited resources, and prioritization of functionality over security can lead to insecure coding…

cs.SE2025

A Comprehensive Multi-Vocal Empirical Study of ML Cloud Service Misuses

Hadil Ben Amor, Manel Abdellatif, Taher Ghaleb

Machine Learning (ML) models are widely used across various domains, including medical diagnostics and autonomous driving. To support this growth, cloud providers offer ML services…