FlyCatcher infers 300 correct stateful runtime checkers from 400 tests across four systems, yielding 2.6x more correct checkers and 5.2x more error detections than prior work.
Las-Casas, Rodrigo Fonseca, and Saravan Rajmohan
6 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 6representative citing papers
A custom LLM agent achieves 94% manually verified success on a new benchmark of 35 software analysis setups, outperforming baselines at 77%, but struggles with stage mixing, error localization, and overestimating its own success.
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
PRAXIS combines LLM-driven structured traversal of service dependency graphs and hammock-block program dependence graphs to improve root-cause analysis accuracy by up to 6.3x while cutting token consumption by 5.3x on 30 real-world cloud incidents.
A case study with 105 network engineers found that an LLM chatbot with RAG, CLI control, and ticket access received positive evaluations in 68.1% of interactions while assisting with building and operating a large demonstration network.
A research roadmap analyzing the current state of search-based software engineering with foundation models, outlining challenges and directions across three integration aspects.
citing papers explorer
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FlyCatcher: Neural Inference of Runtime Checkers from Tests
FlyCatcher infers 300 correct stateful runtime checkers from 400 tests across four systems, yielding 2.6x more correct checkers and 5.2x more error detections than prior work.
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Evaluating LLM Agents on Automated Software Analysis Tasks
A custom LLM agent achieves 94% manually verified success on a new benchmark of 35 software analysis setups, outperforming baselines at 77%, but struggles with stage mixing, error localization, and overestimating its own success.
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Agentic Business Process Management: A Research Manifesto
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
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PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis
PRAXIS combines LLM-driven structured traversal of service dependency graphs and hammock-block program dependence graphs to improve root-cause analysis accuracy by up to 6.3x while cutting token consumption by 5.3x on 30 real-world cloud incidents.
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How Helpful is LLM Assistance in Network Operations? A Case Study at a Large Demonstration Network
A case study with 105 network engineers found that an LLM chatbot with RAG, CLI control, and ticket access received positive evaluations in 68.1% of interactions while assisting with building and operating a large demonstration network.
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Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmap
A research roadmap analyzing the current state of search-based software engineering with foundation models, outlining challenges and directions across three integration aspects.