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Can LLMs Detect Display Issues? Uncovering the Impact of Prompting Techniques

Year: 2025

Type: conference-paper

Abstract: While Large Language Models (LLMs) offer a promising, costeffective alternative to conventional methods for detecting UI display issues, the effectiveness of various prompting techniques has not been systematically analyzed.This paper investigates the impact of various prompting techniques on the performance of LLMs in identifying UI display issues.Our analysis reveals that while some techniques significantly boost detection performance, others show minimal impact, and certain issue types, like Misalignment, remain challenging for all tested approaches.

Source: ACM Symposium on User Interface Software and Technology (UIST)

DOI: 10.1145/3746058.3758415

Authors: Ayoung Choi, Jongwook Jeong

Institution: Jeonbuk National University

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W7084090389

FWCI:

Cites: 5

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