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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Empirical Software Engineer- ing 14, 131–164
12 Pith papers cite this work, alongside 3,793 external citations. Polarity classification is still indexing.
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Noise from quantum hardware simulators significantly alters mutant detection distances, making equivalent mutants harder to separate from faults, with output-distribution metrics reaching 73.03% accuracy and 74.89% F1-score under device-specific thresholds.
Across 2,923 GitHub repositories, context files - especially AGENTS.md and CLAUDE.md - dominate agentic-tool configuration, while advanced mechanisms like Skills and Subagents are rarely used and mostly static.
A composable DSL for describing sampling workflows on code repositories enables explicit specification and statistical reasoning about the generalizability of empirical software engineering findings.
LLM approaches ExArch and ArTEMiS reach F1 scores of 0.86 and 0.81 for architecture entity recognition and traceability, matching or approaching baselines that require manual models.
Mixed-methods study of agile teams finds fragmented practices and organizational barriers limit neurodivergent inclusion despite agile methods' potential.
Hermes uses multi-agent LLMs to detect 2450 documentation and REST smells across 600 OpenAPI endpoints, demonstrating that structurally valid microservice APIs are often not semantically ready for agent consumption.
Interviews in a semiconductor company reveal 16 collaboration and communication challenges in ML engineering teams, with unclear roles and responsibilities as the top issue, and list effective mitigation practices under hardware-driven constraints.
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
Qualitative interview study of 16 practitioners finds most companies at Levels 1-2 of agentic AI maturity and identifies a capability-deployment verification gap as the core barrier to production use.
A single-institution case study finds high student GenAI adoption with policy gaps and proposes an iterative AI Adoption Framework for higher education.
Generative AI suitability in qualitative research depends primarily on the approach (small-q positivist/post-positivist or Big Q non-positivist) along with skills, ethics, and personal preferences.
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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Robust Mutation Analysis of Quantum Programs Under Noise
Noise from quantum hardware simulators significantly alters mutant detection distances, making equivalent mutants harder to separate from faults, with output-distribution metrics reaching 73.03% accuracy and 74.89% F1-score under device-specific thresholds.
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Harness Engineering for Agentic AI Coding Tools: An Exploratory Study
Across 2,923 GitHub repositories, context files - especially AGENTS.md and CLAUDE.md - dominate agentic-tool configuration, while advanced mechanisms like Skills and Subagents are rarely used and mostly static.
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Modeling Sampling Workflows for Code Repositories
A composable DSL for describing sampling workflows on code repositories enables explicit specification and statistical reasoning about the generalizability of empirical software engineering findings.
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Who's Who? LLM-assisted Software Traceability with Architecture Entity Recognition
LLM approaches ExArch and ArTEMiS reach F1 scores of 0.86 and 0.81 for architecture entity recognition and traceability, matching or approaching baselines that require manual models.
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Neurodiversity in Agile Teams: Obstacles and Inclusion Barriers
Mixed-methods study of agile teams finds fragmented practices and organizational barriers limit neurodivergent inclusion despite agile methods' potential.
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Making OpenAPI Documentation Agent-Ready: Detecting Documentation and REST Smells with a Multi-Agent LLM System
Hermes uses multi-agent LLMs to detect 2450 documentation and REST smells across 600 OpenAPI endpoints, demonstrating that structurally valid microservice APIs are often not semantically ready for agent consumption.
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Exploring CoCo Challenges in ML Engineering Teams: Insights From the Semiconductor Industry
Interviews in a semiconductor company reveal 16 collaboration and communication challenges in ML engineering teams, with unclear roles and responsibilities as the top issue, and list effective mitigation practices under hardware-driven constraints.
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Relationships Between Trust, Compliance, and Performance for Novice Programmers Using AI Code Generation
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
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Agentic AI in Industry: Adoption Level and Deployment Barriers
Qualitative interview study of 16 practitioners finds most companies at Levels 1-2 of agentic AI maturity and identifies a capability-deployment verification gap as the core barrier to production use.
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A Systematic AI Adoption Framework for Higher Education: From Student GenAI Usage to Institutional Integration
A single-institution case study finds high student GenAI adoption with policy gaps and proposes an iterative AI Adoption Framework for higher education.
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To Vibe Research or Not to Vibe Research? Generative AI in Qualitative Research
Generative AI suitability in qualitative research depends primarily on the approach (small-q positivist/post-positivist or Big Q non-positivist) along with skills, ethics, and personal preferences.