A systematic review of 50 studies identifies 69 LLM-assisted tasks in empirical software engineering, concentrated in data processing and analysis with gaps in human-centered integration and reproducibility reporting.
Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz
5 Pith papers cite this work, alongside 1,900 external citations. Polarity classification is still indexing.
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Proteus uses a multi-level design space and LLM multi-agents to automatically convert desktop visualizations into equivalent mobile versions that preserve readability.
LearnMate^2, an LLM-driven personalized learning support system, improves learning outcomes and user experience over existing online platforms combined with generic LLM assistance in small-scale user studies.
COMPASS formalizes HPC configuration questions as ML tasks on traces, quantifies recommendation trustworthiness, and delivers 65.93% lower average job turnaround time plus 80.93% lower node usage versus prior methods in simulator tests.
MIRAGE improves VLM analysis of multi-figure art by inserting a verifiable structured representation of micro-interactions between spatial grounding and narrative output.
citing papers explorer
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LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda
A systematic review of 50 studies identifies 69 LLM-assisted tasks in empirical software engineering, concentrated in data processing and analysis with gaps in human-centered integration and reproducibility reporting.
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Proteus: Shapeshifting Desktop Visualizations for Mobile via Multi-level Intelligent Adaptation
Proteus uses a multi-level design space and LLM multi-agents to automatically convert desktop visualizations into equivalent mobile versions that preserve readability.
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LearnMate^2: Design and Evaluation of an LLM-powered Personalized and Adaptive Support System for Online Learning
LearnMate^2, an LLM-driven personalized learning support system, improves learning outcomes and user experience over existing online platforms combined with generic LLM assistance in small-scale user studies.
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COMPASS: A Unified Decision-Intelligence System for Navigating Performance Trade-off in HPC
COMPASS formalizes HPC configuration questions as ML tasks on traces, quantifies recommendation trustworthiness, and delivers 65.93% lower average job turnaround time plus 80.93% lower node usage versus prior methods in simulator tests.
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MIRAGE: A Micro-Interaction Relational Architecture for Grounded Exploration in Multi-Figure Artworks
MIRAGE improves VLM analysis of multi-figure art by inserting a verifiable structured representation of micro-interactions between spatial grounding and narrative output.