33 citations · 55 across the 10 of their papers we have counts for
10 papers
Autonomous Large Language Model Agents Enabling Intent-Driven Mobile GUI Testing
Juyeon Yoon, Robert Feldt, Shin Yoo
GUI testing checks if a software system behaves as expected when users interact with its graphical interface, e.g., testing specific functionality or validating relevant use case s…
Large Language Models for Software Engineering: Survey and Open Problems
Angela Fan, Beliz Gokkaya, Mark Harman +4
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LL…
Evaluating Diverse Large Language Models for Automatic and General Bug Reproduction
Sungmin Kang, Juyeon Yoon, Nargiz Askarbekkyzy +1
Bug reproduction is a critical developer activity that is also challenging to automate, as bug reports are often in natural language and thus can be difficult to transform to test…
Just-in-Time Flaky Test Detection via Abstracted Failure Symptom Matching
Gabin An, Juyeon Yoon, Thomas Bach +2
We report our experience of using failure symptoms, such as error messages or stack traces, to identify flaky test failures in a Continuous Integration (CI) pipeline for a large in…
The GitHub Recent Bugs Dataset for Evaluating LLM-based Debugging Applications
Jae Yong Lee, Sungmin Kang, Juyeon Yoon +1
Large Language Models (LLMs) have demonstrated strong natural language processing and code synthesis capabilities, which has led to their rapid adoption in software engineering app…
Learning Test-Mutant Relationship for Accurate Fault Localisation
Jinhan Kim, Gabin An, Robert Feldt +1
Context: Automated fault localisation aims to assist developers in the task of identifying the root cause of the fault by narrowing down the space of likely fault locations. Simula…