[Paper] Unsafe and Unused? A History of Utility Code in Mature Open Source Projects

Source: arXiv - 2604.28146v1

Overview

This study investigates the lifecycle of “util” (utility) files in seven long‑standing open‑source projects, asking whether these catch‑all modules stay useful, become security liabilities, or simply linger unused as the codebase matures. By mining 30‑day snapshots across 147 project‑years, the authors reveal surprising patterns that can help developers make smarter naming and modularization choices today.

Key Contributions

• Large‑scale longitudinal analysis of 1,773 snapshots covering seven mature projects (Linux kernel, Django, FFmpeg, httpd, Struts, systemd, Tomcat).
• Rename‑tracking methodology that follows each util file through renames, moves, and deletions, preserving its full history.
• Empirical evidence that util files are up to 2.75× more likely to be linked to security vulnerabilities than non‑util files.
• Quantitative insights into how util file complexity, developer ownership, and collaboration evolve over time.
• Actionable guidelines for avoiding “unsafe and unused” utility code in new and existing projects.

Methodology

1. Project selection – Seven widely used, actively maintained open‑source systems with at least a decade of Git history.
2. Snapshot creation – Every 30 days a full repository snapshot was taken, yielding 1,773 data points.
3. Util identification – Files whose path contained the substring “util” (case‑insensitive) were flagged.
4. Rename tracking – Using Git’s rename detection, each util file was followed across moves and renames to keep a continuous record of its lifecycle.
5. Metric extraction – For each snapshot the authors measured:
   • Usage (import/call frequency)
   • Complexity (cyclomatic complexity, LOC)
   • Developer activity (number of contributors, churn)
   • Security events (CVEs, commit‑tagged fixes)
6. Statistical analysis – Correlation and survival‑analysis techniques were applied to compare util vs. non‑util files across the measured dimensions.

Results & Findings

• Prevalence: Util files can constitute a sizable chunk of a codebase (e.g., 17.9 % of Tomcat’s files).
• Vulnerability risk: Util files are 2.75× more likely to be implicated in a CVE than other files, even after controlling for size and complexity.
• Longevity vs. churn: Many util files persist for years with minimal changes, suggesting they become “dead weight” rather than actively maintained utilities.
• Complexity growth: Over time, util files tend to accumulate higher cyclomatic complexity than comparable non‑util modules, likely because they become dumping grounds for unrelated helpers.
• Collaboration patterns: Util files often have a broader but shallower contributor base—many developers touch them, but few own them, leading to inconsistent quality and review practices.
• Rename dynamics: Approximately 30 % of util files are renamed or moved at least once, indicating attempts to reorganize or retire them, but many remain under the “util” moniker despite functional drift.

Practical Implications

• Naming discipline: Treat “util” as a temporary label. If a helper grows beyond a single, well‑defined purpose, move it into a domain‑specific package.
• Code review focus: Prioritize util files for security review and static analysis, given their higher vulnerability propensity.
• Ownership assignment: Assign clear owners or “stewards” for utility modules to avoid the “many hands, no plan” problem.
• Refactoring cadence: Schedule periodic audits (e.g., quarterly) to identify stale util code, consolidate duplicated helpers, and prune dead utilities.
• Tooling support: Extend CI pipelines with scripts that flag new files containing “util” and enforce a checklist (purpose statement, unit tests, ownership) before merging.
• Architecture guidance: Encourage developers to design small, cohesive libraries rather than a monolithic util package, which improves testability and reduces attack surface.

Limitations & Future Work

• Naming bias: The study only captures files with “util” in the path; projects that use alternative conventions (e.g., “common”, “helpers”) are not represented.
• Language scope: All seven projects are primarily C, Java, or Python; results may differ for languages with different module systems (e.g., Rust, Go).
• Causality vs. correlation: While util files are associated with higher vulnerability rates, the analysis cannot definitively prove that the naming convention causes the risk.
• Future directions: Extending the methodology to other naming patterns, exploring automated refactoring tools for util cleanup, and investigating the impact of util code on performance and maintainability in large microservice ecosystems.

Authors

• Brandon Keller
• Kaitlin Yandik
• Angela Ngo
• Andy Meneely

Paper Information

• arXiv ID: 2604.28146v1
• Categories: cs.SE
• Published: April 30, 2026
• PDF: Download PDF