2 citations · 2 across the 9 of their papers we have counts for
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What Does an Agentic Software Engineering Benchmark Measure? Profiling Task Demands and Agent Behaviour Beyond What Category Labels Reveal
Radin Shayanfar, Keheliya Gallaba, Ahmed E. Hassan
Agentic software engineering benchmarks are typically summarized by nominal category labels such as "bug fix" or "feature implementation," yet benchmarks carrying the same label ar…
CASPER-Change-Aware Slice Prioritization for Efficient Regression Testing of LLM-based systems
Biruk Asmare Muse, Lionel Briand, Yiwei Lu +1
Regression testing for LLM-based systems poses unique challenges because individual regression instances provide limited information about system-level regressions. A failure in a…
Towards Imputation of Pre-Trained Language Model Metadata using Semantic Fingerprinting
Adekunle Ajibode, Oussama Ben Sghaier, Keheliya Gallaba +2
Pre-trained language models (PTLMs) hosted on platforms such as Hugging Face form complex lineage structures similar to software dependency graphs. However, unlike traditional soft…
Beyond Accuracy: Behavioral Dynamics of Agentic Multi-Hunk Repair
Noor Nashid, Daniel Ding, Keheliya Gallaba +2
Automated program repair has traditionally focused on single-hunk defects, overlooking multi-hunk bugs that are prevalent in real-world systems. Repairing these bugs requires coord…
Building an Open AIBOM Standard in the Wild
Gopi Krishnan Rajbahadur, Keheliya Gallaba, Elyas Rashno +4
Modern software engineering increasingly relies on open, community-driven standards, yet how such standards are created in fast-evolving domains like AI-powered systems remains und…
Towards Reliable Generation of Executable Workflows by Foundation Models
Sogol Masoumzadeh, Keheliya Gallaba, Dayi Lin +1
Recent advancements in Foundation Models (FMs) have demonstrated significant progress in processing complex natural language to perform intricate tasks. Successfully executing thes…
The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware)
Kirill Vasilevski, Benjamin Rombaut, Gopi Krishnan Rajbahadur +10
Foundation Models (FMs) such as Large Language Models (LLMs) are reshaping the software industry by enabling FMware, systems that integrate these FMs as core components. In this KD…
Characterizing Multi-Hunk Patches: Divergence, Proximity, and LLM Repair Challenges
Noor Nashid, Daniel Ding, Keheliya Gallaba +2
Multi-hunk bugs, where fixes span disjoint regions of code, are common in practice, yet remain underrepresented in automated repair. Existing techniques and benchmarks pre-dominant…
Towards Conversational Development Environments: Using Theory-of-Mind and Multi-Agent Architectures for Requirements Refinement
Keheliya Gallaba, Ali Arabat, Dayi Lin +2
Foundation Models (FMs) have shown remarkable capabilities in various natural language tasks. However, their ability to accurately capture stakeholder requirements remains a signif…
Rethinking Software Engineering in the Foundation Model Era: A Curated Catalogue of Challenges in the Development of Trustworthy FMware
Ahmed E. Hassan, Dayi Lin, Gopi Krishnan Rajbahadur +9
Foundation models (FMs), such as Large Language Models (LLMs), have revolutionized software development by enabling new use cases and business models. We refer to software built us…