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An Empirical Study on Challenges for LLM Application Developers

https://doi.org/10.1145/3715007
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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inferredcites →https://doi.org/10.1109/ase56229.2023.00076openalex-snapshot
Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases
inferredcites →https://doi.org/10.1109/ase56229.2023.00096openalex-snapshot
A Closer Look at Different Difficulty Levels Code Generation Abilities of ChatGPT
inferredcites →https://doi.org/10.1109/iccq60895.2024.10576803openalex-snapshot
Assessing the Code Clone Detection Capability of Large Language Models
inferredcites →https://doi.org/10.1109/icse.2019.00122openalex-snapshot
Software Documentation Issues Unveiled
inferredcites →https://doi.org/10.1109/icse48619.2023.00110openalex-snapshot
CCTEST: Testing and Repairing Code Completion Systems
inferredcites →https://doi.org/10.1109/issre.2012.22openalex-snapshot
An Empirical Study of Bugs in Machine Learning Systems
inferredcites →https://doi.org/10.1109/issre.2019.00020openalex-snapshot
An Empirical Study of Common Challenges in Developing Deep Learning Applications
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Challenges in Chatbot Development
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Understanding performance problems in deep learning systems
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Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
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Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)
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InferFix: End-to-End Program Repair with LLMs
inferredcites →https://doi.org/10.1145/3611643.3616321openalex-snapshot
Compatibility Issues in Deep Learning Systems: Problems and Opportunities
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On the Reliability and Explainability of Language Models for Program Generation
inferredcites →https://doi.org/10.1145/3643674openalex-snapshot
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inferredcites →https://doi.org/10.1145/3660771openalex-snapshot
A Quantitative and Qualitative Evaluation of LLM-Based Explainable Fault Localization
inferredcites →https://doi.org/10.1145/3660773openalex-snapshot
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inferredcites →https://doi.org/10.1145/3678167openalex-snapshot
Automatically Recommend Code Updates: Are We There Yet?
inferredcites →https://doi.org/10.1145/3695988openalex-snapshot
Large Language Models for Software Engineering: A Systematic Literature Review
inferredcites →https://doi.org/10.1145/3695993openalex-snapshot
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inferredcites →https://doi.org/10.1145/3697012openalex-snapshot
On the Effectiveness of Large Language Models in Domain-Specific Code Generation
inferredcites →https://doi.org/10.1177/001316446002000104openalex-snapshot
A Coefficient of Agreement for Nominal Scales
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inferredcites →https://doi.org/10.48550/arxiv.2005.11401openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2201.11903openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1007/978-3-032-41627-8_8openalex-snapshot
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A Dynamic Swarm Reputation-Driven Consensus Mechanism for Trustworthy Embodied Intelligent Collaboration
inferred← citeshttps://doi.org/10.1007/s10579-026-09938-4openalex-snapshot
Hallucinations in generative artificial intelligence and large language models: tests, datasets, detection and correction methods
inferred← citeshttps://doi.org/10.1007/s10664-025-10730-1openalex-snapshot
Continuance use of AI coding assistants among South Korean Industry Developers: A survey case study with large language models
inferred← citeshttps://doi.org/10.1016/j.iswa.2026.200733openalex-snapshot
A systematic mapping study of AI agent–Tool communication: protocols, security, and orchestration
inferred← citeshttps://doi.org/10.1016/j.jss.2026.112867openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.visinf.2026.100330openalex-snapshot
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inferred← citeshttps://doi.org/10.1108/ecam-02-2025-0318openalex-snapshot
The impact of professional training on the adoption of LLMs in architectural structural design: a longitudinal study based on UTAUT
inferred← citeshttps://doi.org/10.1109/aiware69974.2025.00024openalex-snapshot
Security in the Wild: An Empirical Analysis of LLM-Powered Applications and Local Inference Frameworks
inferred← citeshttps://doi.org/10.1109/aixse64906.2025.00016openalex-snapshot
Rising Fast, Prone to Risk: How Open-Source LLM-Powered Apps Are Designed and Secured
inferred← citeshttps://doi.org/10.1109/compsac69091.2026.00053openalex-snapshot
Cross-Layer Heterogeneous Information Integration and Representation for Web Vulnerability Analysis using LLM and Static Analysis
inferred← citeshttps://doi.org/10.1109/icoict66265.2025.11193032openalex-snapshot
Implementation of System Code Generation Based on Large Language Model Fine-tune with QLoRA
inferred← citeshttps://doi.org/10.1109/scam67354.2025.00015openalex-snapshot
Testing the Untestable? An Empirical Study on the Testing Process of LLM-Powered Software Systems
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MambaVEC: A Multi-Agent DRL Framework with Mamba for Efficient Long-Term Vehicular Edge Computing Task Offloading
inferred← citeshttps://doi.org/10.1109/tnse.2026.3683862openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tsc.2026.3703848openalex-snapshot
Collaborative Knowledge Editing for Large Language Model Services in Edge-Cloud Computing
inferred← citeshttps://doi.org/10.1142/s1793351x26410059openalex-snapshot
Rising Fast, Prone to Risk: A Comprehensive Study of Security Risks in Open–Source LLM–Powered Applications
inferred← citeshttps://doi.org/10.1145/3742413.3789105openalex-snapshot
Key Considerations for Domain Expert Involvement in LLM Design and Evaluation: An Ethnographic Study
inferred← citeshttps://doi.org/10.1145/3744916.3787781openalex-snapshot
Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspective
inferred← citeshttps://doi.org/10.1145/3774748.3787633openalex-snapshot
Towards Task-Agnostic Evaluation Framework for LLM-Embedded Applications
inferred← citeshttps://doi.org/10.1145/3786228.3786236openalex-snapshot
Exploring Student-AI Interactions in Vibe Coding
inferred← citeshttps://doi.org/10.1145/3787120.3787123openalex-snapshot
MTF: an Open-Source Metamorphic Testing Framework for LLM-based systems
inferred← citeshttps://doi.org/10.1145/3793653.3793786openalex-snapshot
Assisting Developers in the Selection of Generative AI Models
inferred← citeshttps://doi.org/10.1145/3832776openalex-snapshot
A Road Map for Tamed Interactions with Large Language Models
inferred← citeshttps://doi.org/10.1145/3843770openalex-snapshot
BASFuzz: Toward Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
inferred← citeshttps://doi.org/10.2139/ssrn.7576740openalex-snapshot
Large Language Model-Assisted Safe Translation of Ambiguous Power Dispatch Language into Precise Machine Instructions
inferred← citeshttps://doi.org/10.3390/diagnostics16020215openalex-snapshot
Automated Tumor and Node Staging from Esophageal Cancer Endoscopic Ultrasound Reports: A Benchmark of Advanced Reasoning Models with Prompt Engineering and Cross-Lingual Evaluation
inferred← citeshttps://doi.org/10.3390/info16050368openalex-snapshot
Exploring Large Language Models’ Ability to Describe Entity-Relationship Schema-Based Conceptual Data Models
inferred← citeshttps://doi.org/10.3390/info16050378openalex-snapshot
Large Language Models in Systematic Review Screening: Opportunities, Challenges, and Methodological Considerations
inferred← citeshttps://doi.org/10.37745/ejcsit.2013/vol13n284455openalex-snapshot
Scaling AI Infrastructure: From Recommendation Engines to LLM Deployment with Paged Attention
inferred← citeshttps://doi.org/10.5753/sbsi.2026.248579openalex-snapshot
LLMs in Practice: Results from a Survey with Software Development Professionals in Brazil
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