Abdul Ali Bangash

Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild

Zhimin Zhao, Zehao Wang, Abdul Ali Bangash, Bram Adams et autres

Evaluation harnesses are software systems that orchestrate model evaluation by managing model invocation, data loading, metric computation, and result reporting. Despite their critical role in machine learning infrastructure, their operational challenges and engineering concerns have received limited attention so far. We present …

Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild

Zhimin Zhao, Zehao Wang, Abdul Ali Bangash, Bram Adams et autres

Evaluation harnesses are software systems that orchestrate model evaluation by managing model invocation, data loading, metric computation, and result reporting. Despite their critical role in machine learning infrastructure, their operational challenges and engineering concerns have received limited attention so far. We present …

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On the Footprints of Reviewer Bots Feedback on Agentic Pull Requests in OSS GitHub Repositories

Syeda Inbisath Fatima, Yousuf Abrar, Abdul Rehman Tahir, Amelia Nawaz et autres

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 autonomous, thereby making reviewer bots key actors in the assessment of these agentic PRs. However, …

Reliability of AI Bots Footprints in GitHub Actions CI/CD Workflows

Syed Muhammad Ashhar Shah, Sehrish Habib, Muizz Hussain, Maryam Abdul Ghafoor et autres

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 underexplored. Using pull requests (PRs), commits, and repositories from the AIDev dataset, we retrieved associated CI/CD workflow runs …

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Reliability of AI Bots Footprints in GitHub Actions CI/CD Workflows

Syed Muhammad Ashhar Shah, Sehrish Habib, Muizz Hussain, Maryam Abdul Ghafoor et autres

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 underexplored. Using pull requests (PRs), commits, and repositories from the AIDev dataset, we retrieved associated CI/CD workflow runs …

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On the Footprints of Reviewer Bots' Feedback on Agentic Pull Requests in OSS GitHub Repositories

Syeda Kaneez Fatima, Yousuf Abrar, Abdul Rehman Tahir, Amelia Nawaz et autres

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 autonomous, thereby making reviewer bots key actors in the assessment of these agentic PRs. However, …

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Studying the Footprints of AI Coding Agents in Blockchain Repositories

Munim Iftikhar, Maaz Shahid, Shahreyar Ashraf, Muhammad Saqib Ilyas et autres

AI coding agents are rapidly transforming software development, yet researchers do not fully understand their effectiveness in specialized domains. Previous studies examined how these agents contribute code via pull requests (PRs) across repositories from various domains, making it difficult to isolate domain-specific …

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Novice Developers Produce Larger Review Overhead for Project Maintainers while Vibe Coding

Syed Ammar Asdaque, Imran Haider, Muhammad Umar Malik, Maryam Abdul Ghafoor et autres

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 development experience substitute for expert developers? To explore whether developer experience still matters in AI-assisted …

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On the Adoption of AI Coding Agents in Open-source Android and iOS Development

Muhammad Ahmad Khan, Hasnain Ali, Muneeb Rana, Muhammad Saqib Ilyas et autres

AI coding agents are increasingly contributing to software development, yet their impact on mobile development has received little empirical attention. In this paper, we present the first category-level empirical study of agent-generated code in open-source mobile app projects. We analyzed PR acceptance …

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On the synchronization between Hugging Face pre-trained language models and their upstream GitHub repository

Adekunle Ajibode, Abdul Ali Bangash, Oussama Ben Sghaier, Bram Adams et autres

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HAFix: history-augmented large language models for bug fixing

Yu Shi, Abdul Ali Bangash, Emad Fallahzadeh, Bram Adams et autres

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Novice Developers Produce Larger Review Overhead for Project Maintainers while Vibe Coding

Syed Ammar Asdaque, Imran Haider, Muhammad Umar Malik, Maryam Abdul Ghafoor et autres

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 development experience substitute for expert developers? To explore whether developer experience still matters in AI-assisted …