20 citations · 31 across the 12 of their papers we have counts for
12 papers
Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild
Zhimin Zhao, Zehao Wang, Abdul Ali Bangash +2
Evaluation harnesses are software systems that orchestrate model evaluation by managing model invocation, data loading, metric computation, and result reporting. Despite their crit…
On the Footprints of Reviewer Bots Feedback on Agentic Pull Requests in OSS GitHub Repositories
Syeda Kaneez Fatima, Yousuf Abrar, Abdul Rehman Tahir +3
Autonomous coding agents are reshaping software development by creating pull requests (PRs) on GitHub, referred to as agentic PRs. In parallel, the review process is also becoming…
Reliability of AI Bots Footprints in GitHub Actions CI/CD Workflows
Syed Muhammad Ashhar Shah, Sehrish Habib, Muizz Hussain +2
Continuous Integration and Deployment (CI/CD) workflows are central to modern software delivery, yet the reliability of agentic AI bots operating within these workflows remain unde…
Novice Developers Produce Larger Review Overhead for Project Maintainers while Vibe Coding
Syed Ammar Asdaque, Imran Haider, Muhammad Umar Malik +2
AI coding agents allow software developers to generate code quickly, which raises a practical question for project managers and open source maintainers: can vibe coders with less d…
The State of the SBOM Tool Ecosystems: A Comparative Analysis of SPDX and CycloneDX
Zhimin Zhao, Abdul Ali Bangash, Tongxu Ge +3
Software Bills of Materials (SBOMs) improve software release transparency by documenting components and dependencies, but their practical value depends on the tools that generate,…
Understanding Prompt Management in GitHub Repositories: A Call for Best Practices
Hao Li, Hicham Masri, Filipe R. Cogo +3
The rapid adoption of foundation models (e.g., large language models) has given rise to promptware, i.e., software built using natural language prompts. Effective management of pro…
On the synchronization between Hugging Face pre-trained language models and their upstream GitHub repository
Adekunle Ajibode, Abdul Ali Bangash, Oussama Ben Sghaier +2
Pre-trained language models (PTLMs) have transformed natural language processing (NLP), enabling major advances in tasks such as text generation and translation. Similar to softwar…
HAFix: History-Augmented Large Language Models for Bug Fixing
Yu Shi, Abdul Ali Bangash, Emad Fallahzadeh +2
Recent studies have explored the performance of Large Language Models (LLMs) on various Software Engineering (SE) tasks, such as code generation and bug fixing. However, these appr…
Towards Semantic Versioning of Open Pre-trained Language Model Releases on Hugging Face
Adekunle Ajibode, Abdul Ali Bangash, Filipe Roseiro Cogo +2
The proliferation of open Pre-trained Language Models (PTLMs) on model registry platforms like Hugging Face (HF) presents both opportunities and challenges for companies building p…
On the Workflows and Smells of Leaderboard Operations (LBOps): An Exploratory Study of Foundation Model Leaderboards
Zhimin Zhao, Abdul Ali Bangash, Filipe Roseiro Côgo +2
Foundation models (FM), such as large language models (LLMs), which are large-scale machine learning (ML) models, have demonstrated remarkable adaptability in various downstream so…
An Empirical Study of Challenges in Machine Learning Asset Management
Zhimin Zhao, Yihao Chen, Abdul Ali Bangash +2
In machine learning (ML), efficient asset management, including ML models, datasets, algorithms, and tools, is vital for resource optimization, consistent performance, and a stream…
The State of Documentation Practices of Third-party Machine Learning Models and Datasets
Ernesto Lang Oreamuno, Rohan Faiyaz Khan, Abdul Ali Bangash +2
Model stores offer third-party ML models and datasets for easy project integration, minimizing coding efforts. One might hope to find detailed specifications of these models and da…