24 papers
AI-to-AI Code Reviews of GitHub Pull Requests
Niruthiha Selvanayagam, Taher A. Ghaleb
AI coding agents are increasingly integrated into software development workflows, operating on both sides of the pull-request (PR) process: AI authoring agents create or modify PRs…
A Large-Scale Longitudinal Study of Multi-CI Service Adoption
Taher A. Ghaleb, Rasha Bin-Thalab
Continuous Integration (CI) adoption has evolved from a single practice into a broad landscape of competing services, and many projects no longer rely on a single CI service. Howev…
Studying Developer Perceptions on the Potential of CI Recommendation Systems
Osamah H. Alaini, Taher A. Ghaleb
Continuous Integration (CI) is central to modern software development, yet developers often struggle to choose the most suitable CI service. Prior work has identified barriers to C…
Doc2CI: A Multi-Service Study of CI Configuration Generation Using Large Language Models
Taher A. Ghaleb
Adopting Continuous Integration (CI) often requires writing YAML configurations that are error-prone and challenging to maintain. Despite increasing LLM use in software engineering…
AgenTag: Attribution of AI Coding Agents from Behavioral Fingerprints
Taher A. Ghaleb
AI coding agents increasingly author pull requests (PRs), often under developers' own accounts, obscuring who actually produced a change. Reliable attribution is important for repo…
From Assistance to Agency: Rethinking Autonomy and Control in CI/CD Pipelines
Marcus Emmanuel Barnes, Taher A. Ghaleb, Safwat Hassan
AI agents are assuming active roles in Continuous Integration and Continuous Deployment (CI/CD) workflows, yet the research community lacks a shared vocabulary for describing what…
How Compliant Are GitHub Actions Workflows? A Checklist-Based Study with LLM-Assisted Auditing
Edward Abrokwah, Taher A. Ghaleb
GitHub Actions (GHA) CI workflows are critical infrastructure, but current tooling offers only syntactic or heuristic checks and does not enforce documented best practices for secu…
Mapping GitHub Sponsorships: A Longitudinal Observatory for Open-Source Sustainability
Rylan Hiltz, Taher A. Ghaleb
Financial sustainability is vital for open-source software, yet systematic research on funding remains limited. GitHub Sponsors, launched in 2019 as a direct developer-to-developer…
A Vision for Context-Aware CI Adoption Decisions
Osamah H. Alaini, Taher A. Ghaleb
Continuous Integration (CI) is widely adopted in modern software development, yet adoption decisions are often made without systematic consideration of project context. Platforms s…
Android Instrumentation Testing in Continuous Integration: Practices, Patterns, and Performance
Hamid Parsazadeh, Taher A. Ghaleb, Safwat Hassan
Android instrumentation tests (end-to-end tests that run on a device or emulator) can catch problems that simpler tests miss. However, running these tests automatically in continuo…
MLmisFinder: A Specification and Detection Approach of Machine Learning Service Misuses
Hadil Ben Amor, Niruthiha Selvanayagam, Manel Abdellatif +2
Machine Learning (ML) cloud services, offered by leading providers such as Amazon, Google, and Microsoft, enable the integration of ML components into software systems without buil…
Role of CI Adoption in Mobile App Success: An Empirical Study of Open-Source Android Projects
Xiaoxin Zhou, Taher A. Ghaleb, Safwat Hassan
Mobile apps face strong pressure for fast and reliable updates. Continuous Integration (CI) helps automate builds, tests, and releases, but its impact on mobile development remains…
LogSieve: Task-Aware CI Log Reduction for Sustainable LLM-Based Analysis
Marcus Emmanuel Barnes, Taher A. Ghaleb, Safwat Hassan
Logs are essential for understanding Continuous Integration (CI) behavior, particularly for diagnosing build failures and performance regressions. Yet their growing volume and verb…
Self-Admitted Technical Debt in LLM Software: An Empirical Comparison with ML and Non-ML Software
Niruthiha Selvanayagam, Taher A. Ghaleb, Manel Abdellatif
Self-admitted technical debt (SATD), referring to comments flagged by developers that explicitly acknowledge suboptimal code or incomplete functionality, has received extensive att…
The Promise and Reality of Continuous Integration Caching: An Empirical Study of Travis CI Builds
Taher A. Ghaleb, Daniel Alencar da Costa, Ying Zou
Continuous Integration (CI) provides early feedback by automatically building software, but long build durations can hinder developer productivity. CI services use caching to speed…
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…
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…
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…
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,…
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…
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…
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…
CI/CD Configuration Practices in Open-Source Android Apps: An Empirical Study
Taher A. Ghaleb, Osamah Abduljalil, Safwat Hassan
Continuous Integration and Continuous Delivery (CI/CD) is a well-established practice that automatically builds, tests, packages, and deploys software systems. To adopt CI/CD, soft…
A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits
Steffen Herbold, Alexander Trautsch, Benjamin Ledel +45
Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only…