Cover Image

Exploring Direct Instruction and Summary-Mediated Prompting in LLM-Assisted Code Modification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tang, Ningzhi, Smith, Emory, Huang, Yu, McMillan, Collin, Li, Toby Jia-Jun
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Human-Computer Interaction
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

NaturalEdit: Code Modification through Direct Interaction with Adaptive Natural Language Representation
by: Tang, Ningzhi, et al.
Published: (2025)

A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions
by: Tang, Ningzhi, et al.
Published: (2024)

Programming by Chat: A Large-Scale Behavioral Analysis of 11,579 Real-World AI-Assisted IDE Sessions
by: Tang, Ningzhi, et al.
Published: (2026)

How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions
by: Tang, Ningzhi, et al.
Published: (2026)

EyeTrans: Merging Human and Machine Attention for Neural Code Summarization
by: Zhang, Yifan, et al.
Published: (2024)

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
by: Zhang, Yifan, et al.
Published: (2025)

Context-aware Code Summary Generation
by: Su, Chia-Yi, et al.
Published: (2024)

Gendered Prompting and LLM Code Review: How Gender Cues in the Prompt Shape Code Quality and Evaluation
by: Janzen, Lynn, et al.
Published: (2026)

Programmer Visual Attention During Context-Aware Code Summarization
by: Wallace, Robert, et al.
Published: (2024)

Cognitive Biases in LLM-Assisted Software Development
by: Zhou, Xinyi, et al.
Published: (2026)

NeuroSync: Intent-Aware Code-Based Problem Solving via Direct LLM Understanding Modification
by: Zhang, Wenshuo, et al.
Published: (2025)

Explaining Code with a Purpose: An Integrated Approach for Developing Code Comprehension and Prompting Skills
by: Denny, Paul, et al.
Published: (2024)

"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code
by: Zi, Yangtian, et al.
Published: (2025)

GazeCopilot: Evaluating Novel Gaze-Informed Prompting for AI-Supported Code Comprehension and Readability
by: Elfares, Yasmine, et al.
Published: (2025)

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions
by: Schön, David, et al.
Published: (2026)

Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering
by: Zhang, Tanghaoran, et al.
Published: (2024)

Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness
by: Salmon, Audrey, et al.
Published: (2025)

Pre-Filtering Code Suggestions using Developer Behavioral Telemetry to Optimize LLM-Assisted Programming
by: Awad, Mohammad Nour Al, et al.
Published: (2025)

GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant
by: Merten, Gaspard, et al.
Published: (2025)

Semantic Neighborhood Density and Eye Gaze Time in Human Programmer Attention
by: Wallace, Robert, et al.
Published: (2026)

Generating Complex Code Analyzers from Natural Language Questions
by: Nazari, Amirmohammad, et al.
Published: (2026)

EcoAssist: Embedding Sustainability into AI-Assisted Frontend Development
by: Barrocas, André, et al.
Published: (2026)

Human Attention During Localization of Memory Bugs in C Programs
by: Smith, Emory, et al.
Published: (2025)

A Picture Is Worth a Thousand Words: Exploring Diagram and Video-Based OOP Exercises to Counter LLM Over-Reliance
by: Cipriano, Bruno Pereira, et al.
Published: (2024)

From Prompt to Product: A Human-Centered Benchmark of Agentic App Generation Systems
by: Ortiz, Marcos, et al.
Published: (2025)

Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering
by: Li, Ziyou, et al.
Published: (2025)

PriviSense: A Frida-Based Framework for Multi-Sensor Spoofing on Android
by: Khalilov, Ibrahim, et al.
Published: (2026)

Accodemy: AI Powered Code Learning Platform to Assist Novice Programmers in Overcoming the Fear of Coding
by: Aamina, M. A. F., et al.
Published: (2025)

CodeA11y: Making AI Coding Assistants Useful for Accessible Web Development
by: Mowar, Peya, et al.
Published: (2025)

Using an LLM to Help With Code Understanding
by: Nam, Daye, et al.
Published: (2023)

Can Developers Prompt? A Controlled Experiment for Code Documentation Generation
by: Kruse, Hans-Alexander, et al.
Published: (2024)

Is Vibe Coding the Future? An Empirical Assessment of LLM Generated Codes for Construction Safety
by: Uddin, S M Jamil
Published: (2026)

Enhancing Code LLM Training with Programmer Attention
by: Zhang, Yifan, et al.
Published: (2025)

Automatic Bias Detection in Source Code Review
by: Alebachew, Yoseph Berhanu, et al.
Published: (2025)

Assessing Consensus of Developers' Views on Code Readability
by: Sergeyuk, Agnia, et al.
Published: (2024)

Prototyping with Prompts: Emerging Approaches and Challenges in Generative AI Design for Collaborative Software Teams
by: Subramonyam, Hari, et al.
Published: (2024)

Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks
by: Etsenake, Deborah, et al.
Published: (2024)

PerspectiveCoach: Exploring LLMs for Developer Reflection
by: Olson, Lauren, et al.
Published: (2026)

Exploring Developer Experience Factors in Software Ecosystems
by: Zacarias, Rodrigo Oliveira, et al.
Published: (2025)

Bug Detective and Quality Coach: Developers' Mental Models of AI-Assisted IDE Tools
by: Buono, Paolo, et al.
Published: (2025)