1 citations · 1 across the 6 of their papers we have counts for
6 papers
Who Writes the Docs in SE 3.0? Agent vs. Human Documentation Pull Requests
Kazuma Yamasaki, Joseph Ayobami Joshua, Tasha Settewong +3
As software engineering moves toward SE3.0, AI agents are increasingly used to carry out development tasks and contribute changes to software projects. It is therefore important to…
Understanding the Characteristics of LLM-Generated Property-Based Tests in Exploring Edge Cases
Hidetake Tanaka, Haruto Tanaka, Kazumasa Shimari +1
As Large Language Models (LLMs) increasingly generate code in software development, ensuring the quality of LLM-generated code has become important. Traditional testing approaches…
Round Outcome Prediction in VALORANT Using Tactical Features from Video Analysis
Nirai Hayakawa, Kazumasa Shimari, Kazuma Yamasaki +3
Recently, research on predicting match outcomes in esports has been actively conducted, but much of it is based on match log data and statistical information. This research targets…
eye2vec: Learning Distributed Representations of Eye Movement for Program Comprehension Analysis
Haruhiko Yoshioka, Kazumasa Shimari, Hidetake Uwano +1
This paper presents eye2vec, an infrastructure for analyzing software developers' eye movements while reading source code. In common eye-tracking studies in program comprehension,…
Uncovering Intention through LLM-Driven Code Snippet Description Generation
Yusuf Sulistyo Nugroho, Farah Danisha Salam, Brittany Reid +3
Documenting code snippets is essential to pinpoint key areas where both developers and users should pay attention. Examples include usage examples and other Application Programming…
Using LLMs for Security Advisory Investigations: How Far Are We?
Bayu Fedra Abdullah, Yusuf Sulistyo Nugroho, Brittany Reid +3
Large Language Models (LLMs) are increasingly used in software security, but their trustworthiness in generating accurate vulnerability advisories remains uncertain. This study inv…