activity
20162026
most citedDo Developers Update Their Library Dependencies? An Empirical Study on the Impact of Security Advisories on Library Migration

348 citations · 583 across the 98 of their papers we have counts for

collaborators

105 papers

cs.SE2026

The Role of Agentic Instruction Categories for Code Generation: A Study of Five Python Libraries

Warren Gerald Polandra, Yoshiki Higo, Raula Gaikovina Kula

Agentic coding systems increasingly rely on repository-level agent files, such as AGENTS.md, to communicate project knowledge and developer intent. However, it remains unclear whic…

cs.SE2026

Agentic Dependency Transformations: Lessons from an Exploratory Case Study of Flask

Kaya Kitada, Yoshiki Higo, Raula Gaikovina Kula

Modern software relies heavily on third-party libraries, requiring maintainers to balance the benefits of reuse against dependency-related maintenance and risk. We define dependenc…

cs.SE2026

An Exploratory Study of Dependabot Cooldown Adoption in Open-Source GitHub Projects

Hidetake Tanaka, Rikuto Tsuchida, Kazumasa Shimari +2

Automated dependency updates can rapidly propagate malicious package releases before maintainers and the broader community have enough time to detect them. In July 2025, GitHub mad…

cs.SE2026

Cross-Ecosystem Packages As Multilingual: Prevalence, Architecture, and Health

Xiangxi Li, Olivier Nourry, Yoshiki Higo +1

Modern software development increasingly relies on using multiple programming languages. Some software packages are published to multiple package ecosystems such as NPM for JavaScr…

cs.SE2026

Agent ATO: Visualizing Agent Interaction Timelines from Logs

Takuto Kawamoto, Yoshiki Higo, Raula Gaikovina Kula

AI coding agents are becoming part of developers' workflows, but their behavior is difficult to understand from final code changes alone. During a task, agents interact with softwa…

cs.SE2026

Maintenance Signals in AI-Assisted GitHub Repositories: Evidence from GenAI Adopters

Rikuto Tsuchida, Youmei Fan, Kazumasa Shimari +3

Generative artificial intelligence (GenAI) can reduce code-generation effort, but it may shift work to documentation, validation, debugging, and maintenance. We study observable ma…