arXiv subjects

Yutaro Kashiwa

Publications and source records attributed to Yutaro Kashiwa.

23 records · Page 2Linked to original sources

arXiv2026

Does Programming Language Matter? An Empirical Study of Fuzzing Bug Detection

Fuzzing has become a popular technique for automatically detecting vulnerabilities and bugs by generating unexpected inputs. In recent years, the fuzzing process has been integrated into continuous integration workflows (i.e., continuous fuzzing), enabling short and frequent testing cycles. Despite its widespread adoption, prior research has not examined whether the effectiveness of continuous fuzzing varies across programming languages. This study conducts a large-scale cross-language analysis to examine how fuzzing bug characteristics and detection efficiency differ among languages. We analyze 61,444 fuzzing bugs and 999,248 builds from 559 OSS-Fuzz projects categorized by primary language. Our findings reveal that (i) C++ and Rust exhibit higher fuzzing bug detection frequencies, (ii) Rust and Python show low vulnerability ratios but tend to expose more critical vulnerabilities, (iii) crash types vary across languages and unreproducible bugs are more frequent in Go but rare in Rust, and (iv) Python attains higher patch coverage but suffers from longer time-to-detection. These results demonstrate that fuzzing behavior and effectiveness are strongly shaped by language design, providing insights for language-aware fuzzing strategies and tool development.

cs.SE↗

arXiv2025

Large-Scale Empirical Analysis of Continuous Fuzzing: Insights from 1 Million Fuzzing Sessions

Software vulnerabilities are constantly being reported and exploited in software products, causing significant impacts on society. In recent years, the main approach to vulnerability detection, fuzzing, has been integrated into the continuous integration process to run in short and frequent cycles. This continuous fuzzing allows for fast identification and remediation of vulnerabilities during the development process. Despite adoption by thousands of projects, however, it is unclear how continuous fuzzing contributes to vulnerability detection. This study aims to elucidate the role of continuous fuzzing in vulnerability detection. Specifically, we investigate the coverage and the total number of fuzzing sessions when fuzzing bugs are discovered. We collect issue reports, coverage reports, and fuzzing logs from OSS-Fuzz, an online service provided by Google that performs fuzzing during continuous integration. Through an empirical study of a total of approximately 1.12 million fuzzing sessions from 878 projects participating in OSS-Fuzz, we reveal that (i) a substantial number of fuzzing bugs exist prior to the integration of continuous fuzzing, leading to a high detection rate in the early stages; (ii) code coverage continues to increase as continuous fuzzing progresses; and (iii) changes in coverage contribute to the detection of fuzzing bugs. This study provides empirical insights into how continuous fuzzing contributes to fuzzing bug detection, offering practical implications for future strategies and tool development in continuous fuzzing.

cs.SE↗

arXiv2025

An Empirical Study of Security-Policy Related Issues in Open Source Projects

GitHub recommends that projects adopt a security file that outlines vulnerability reporting procedures. However, the effectiveness and operational challenges of such files are not yet fully understood. This study aims to clarify the challenges that security files face in the vulnerability reporting process within open-source communities. Specifically, we classified and analyzed the content of 711 randomly sampled issues related to security files. We also conducted a quantitative comparative analysis of the close time and number of responses for issues concerning six community health files, including security files. Our analysis revealed that 79.5% of security file-related issues were requests to add the file, and reports that included links were closed, with a median time that was 2 days shorter. These findings offer practical insights for improving security reporting policies and community management, ultimately contributing to a more secure open-source ecosystem.

cs.SE↗

arXiv2025

Detecting and Characterizing Low and No Functionality Packages in the NPM Ecosystem

Trivial packages, small modules with low functionality, are common in the npm ecosystem and can pose security risks despite their simplicity. This paper refines existing definitions and introduce data-only packages that contain no executable logic. A rule-based static analysis method is developed to detect trivial and data-only packages and evaluate their prevalence and associated risks in the 2025 npm ecosystem. The analysis shows that 17.92% of packages are trivial, with vulnerability levels comparable to non-trivial ones, and data-only packages, though rare, also contain risks. The proposed detection tool achieves 94% accuracy (macro-F1 0.87), enabling effective large-scale analysis to reduce security exposure. This findings suggest that trivial and data-only packages warrant greater attention in dependency management to reduce potential technical debt and security exposure.

cs.SE↗

arXiv2025

On the Use of Agentic Coding Manifests: An Empirical Study of Claude Code

Agentic coding tools receive goals written in natural language as input, break them down into specific tasks, and write/execute the actual code with minimal human intervention. Key to this process are agent manifests, configuration files (such as Claude.md) that provide agents with essential project context, identity, and operational rules. However, the lack of comprehensive and accessible documentation for creating these manifests presents a significant challenge for developers. We analyzed 253 Claude.md files from 242 repositories to identify structural patterns and common content. Our findings show that manifests typically have shallow hierarchies with one main heading and several subsections, with content dominated by operational commands, technical implementation notes, and high-level architecture.

cs.SE↗