Source-linked AI summary
An Exploratory Study of Dependabot Cooldown Adoption in Open-Source GitHub Projects
Hidetake Tanaka, Rikuto Tsuchida, Kazumasa Shimari, Raula Gaikovina Kula, Kenichi Matsumoto
TL;DR
Rapid automated dependency updates can propagate malicious releases before detection, while evidence about early Dependabot cooldown adoption remains limited. This exploratory study examines adoption, motivations, and configuration among popular public GitHub repositories, finding that early users generally favor simple delays over fine-grained controls.
Problem
Empirical evidence is limited on how Dependabot cooldown is adopted and configured in practice, although understanding its use supports future effectiveness studies and tool-design decisions.
Method
The study conducts an exploratory empirical analysis of early cooldown adoption, motivations, adopter characteristics, and configurations across popular public GitHub repositories.
Results
135 adopters among 1,462 repositories showed limited but growing adoption; security concerns dominated identified motivations, and most retained configurations used one general delay, commonly 7 days.
Takeaways & Limitations
Early adopters use cooldown primarily as a low-configuration safeguard, suggesting simple defaults and validated ecosystem support rather than assuming 7 days is optimal.
Takeaways & Limitations
The findings describe Dependabot users on public GitHub repositories and cannot be generalized to dependency-management practices on other platforms.
Abstract
from arXiv · showhide
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 made Dependabot cooldown generally available as a defense against software supply chain attacks. However, the effects of its early adoption remain unknown. In this exploratory study, we empirically examine how popular open-source GitHub repositories adopt and configure the feature and investigate their motivations. We find that security concerns motivated 83 of 92 adoption events with known motivations. Security linter warnings triggered 43 of 75 security-only adoptions. Among 251 ecosystems within repositories that retained cooldown, 97.2% set a general delay. Of these, 64.3% used seven days, while use of each update type setting was below 10%. Early adopters therefore favor simple default delays over fine-grained controls. These findings suggest that tools could provide robust defaults reflecting ecosystem support and reserve fine-grained controls for dependencies with clear update priorities.
1 Introduction
This study examines early Dependabot cooldown adoption because empirical evidence about its uptake and practical configuration remains limited. It focuses on how popular open-source GitHub repositories adopt, configure, and motivate a single cross-ecosystem defense feature.
- 1 Introduction: Dependabot cooldown introduces configurable delays before newly published package versions are automatically adopted, targeting supply chain risk.GitHub describes benefits including reduced update noise, responsiveness to critical security patches, SemVer-level control, and flexible scheduling.
- 1 Introduction: Empirical evidence remains limited on how widely Dependabot cooldown is adopted or configured, motivating study of adopters, configurations, and evolution.The study frames this evidence as a basis for future effectiveness studies and tool-design decisions.
- 1 Introduction: The study analyzes early adoption among top-starred public GitHub repositories and compares use across package ecosystems under one configuration schema.A single tool supports multiple ecosystems while avoiding cross-tool heterogeneity.
- 1 Introduction: The research questions cover how projects adopt and abandon cooldown, what distinguishes adopters, and how adopters configure and adjust it.These questions organize the study around adoption, adopter characteristics, and configuration choices.
- 1 Introduction: The contributions combine quantitative and qualitative analysis of adoption, motivations, project characteristics, and configuration mechanisms among early adopters.The study also considers Dependabot’s stated benefits, including SemVer-level granularity and flexible scheduling.
2 Related Work
Prior work documents supply chain attacks, dependency-bot benefits and overhead, update lags, and ecosystem differences, but leaves cooldown adoption and configuration insufficiently understood. This study addresses that gap by examining deliberate cooldown use as a proactive defense across ecosystems.
- 2 Related Work: Supply chain attacks can enter through malicious or destructive package releases and spread rapidly through dependency chains to downstream projects.Prior work describes registry attacks, compromised popular packages, typosquatting, and malicious updates from legitimate maintainers.
- 2 Related Work: Cooldown adoption and configuration remain insufficiently understood despite research on supply chain attacks, dependency bots, and their overhead.The paper positions its contribution as empirical investigation of how projects configure and adopt cooldown features.
- 2 Related Work: Dependency-management bots increase update activity but also impose notification and triage costs on maintainers.Prior studies report more frequent updates, many unmerged automated pull requests, interruptions, and notifications that demand attention without corresponding benefit.
- 2 Related Work: Fine-grained cooldown by SemVer level relies on conventions that may not consistently reflect breaking changes across ecosystems.Prior studies report breaking changes in minor and patch releases and differing ecosystem practices around compatibility.
- 2 Related Work: Dependency update lag is distinct from cooldown: lag reflects delayed adoption from inattention or reluctance, whereas cooldown is an intentional protective delay.The study therefore focuses on deliberate adoption and configuration of cooldown as a proactive defense strategy.
- 2 Related Work: Cooldown mechanisms have earlier stability-oriented precedents, but newer Dependabot and package-manager features are explicitly motivated by supply chain security.Renovate’s stabilityDays addressed package retraction risk, contrasting with the security rationale of newer features.
3 Study Design
The study examines early Dependabot cooldown adoption across popular GitHub repositories using configuration histories, repository metadata, and development artifacts. It filters repositories for valid, active Dependabot configurations, classifies adoption states, and analyzes adoption, adopter characteristics, and configuration changes.
- Study scope: The study analyzes early Dependabot cooldown adoption across package ecosystems supported by Dependabot using top-starred open-source GitHub repositories.The design combines data collection with quantitative and qualitative analyses addressing adoption, adopter characteristics, and configuration choices.
- Adoption classification: Repositories were classified as non-adopters, continuous adopters, re-adopted adopters, or abandoned adopters from configuration histories and cutoff status.The same states were applied to ecosystems, while removal of an ecosystem’s entire updates entry was treated as discontinued management rather than cooldown abandonment.
- Research questions: RQ2 treats repository adoption status as the outcome and uses repository characteristics, dependency measures, Dependabot activity, and pre-GA configuration edits as explanatory variables.The pre-GA edit rate avoids counting the cooldown-introduction commit as evidence of prior maintenance activity.
- Configuration analysis: RQ3 measures cooldown settings and later changes at the ecosystem-within-repository level, using minimum values across multiple cooldowns in the same ecosystem.The analyzed fields include default-days, SemVer-level delays, and include or exclude lists; additions and removals are counted through configuration-history changes.
4 Results
Among 1,462 repositories, 135 adopted Dependabot cooldown, with security the dominant known motivation and simple seven-day defaults prevailing among retained configurations.
- RQ1: Adoption Motivations: 83 of 92 adoption events with known motivations involved security, including 43 of 75 security-only events triggered by security-linter warnings.Security-only events comprised 43 Security (Linter) and 32 Security (No-Linter) cases; eight additional events combined security with maintenance concerns.
- RQ1: Adoption and Abandonment: 135 of 1,462 repositories adopted cooldown, and no repository abandoned it entirely during the observation window.Observed removals were temporary or ecosystem-specific, commonly reflecting operational or compatibility problems; every repository-level adopter retained cooldown in at least one ecosystem at the cutoff.
- RQ2: Adopter Characteristics: Adopters had significantly more stars, contributors, dependencies, and bot pull requests, plus higher organization-ownership and SECURITY.md rates than non-adopters.Among repositories with merged Dependabot pull requests, adopters also had shorter merge times, although the bot-pull-request difference had the only medium effect size.
- RQ2: Adopter Characteristics: Adjusted estimates associated adoption with contributors, bot pull requests, and SECURITY.md presence, while Go, Java, and TypeScript showed lower odds than Python.Adjusted odds ratios were 1.45, 1.85, and 1.68 for the three positive associations, and 0.36, 0.33, and 0.45 for Go, Java, and TypeScript; these observational associations do not establish causality.
- RQ3: Configuration Choices: 97.2% of 251 retained ecosystems set default-days, and 64.3% of those used seven days, while each SemVer-level setting remained below 10%.Post-adoption changes were rare: default-days increases moved from three or four days to seven, while SemVer-level settings were only removed; rare ecosystem-specific differences reflected update priorities.
5 Discussion
Early adopters generally use Dependabot cooldown as a simple delay, while security linters mediate many adoption decisions. Interpretation is bounded by incomplete motivation evidence, observational associations, measurement limits, and the study’s focus on public, popular GitHub repositories.
- 5.1 Interpretation of Results: Security concerns motivated 83 of 92 adoption events with known motivations, but 43 of 135 first-time adoptions were Unknown.Even treating every Unknown event as non-security motivated leaves security motivations in 61.5% of all adoptions.
- 5.2 Implications for Tool Designers: The common seven-day default is an empirical reference point, not evidence that seven days is optimal.The discussion links this preference to low configuration burden and recommends simple candidate settings before fine-grained controls.
- 5.2 Implications for Tool Designers: Unsupported cooldown settings can prevent Dependabot from running, so shared configurations should verify ecosystem support and fit the inherited update workflow.The study recommends that unsupported settings fail clearly without stopping Dependabot as a whole.
- 5.4.1 Construct Validity: The reported abandonment rate is a lower bound because the measure excludes repositories whose entire Dependabot configuration was deleted.The study counts removal only when cooldown disappears while Dependabot remains configured.
- 5.4.1 Construct Validity: Cross-sectional regression results show associations rather than causality, and measured pull-request activity may itself be affected by cooldown adoption.Sensitivity analyses also cover narrower repository subsets rather than random subsets.
6 Conclusion
This exploratory study establishes an empirical baseline for early Dependabot cooldown adoption, finding limited but growing adoption, security-driven motivations, and predominantly simple configurations. Its evidence is restricted to popular public GitHub repositories over approximately ten months and does not establish that cooldown prevents supply chain incidents.
- Security concerns dominate identified adoption motivations, while adoption remains associated with more contributors, more bot pull requests, and a SECURITY.md file after adjustment.
- Most configurations use one general delay, commonly seven days, indicating that early adopters favor low-configuration safeguards over customized scheduling policies.
- Tool designers should favor simple defaults, validate ecosystem support, and report invalid configurations clearly.
- The evidence covers popular public GitHub repositories during approximately ten months and does not show that cooldown prevents supply chain incidents.
Funding
The study was supported by JST BOOST and JSPS KAKENHI grants.
- The work was supported by JST BOOST and JSPS KAKENHI grants.
Competing interests
The authors report no relevant financial or non-financial competing interests.
- The authors report no relevant financial or non-financial interests to disclose.
Ethics approval
Ethics approval was not applicable because the study used publicly available repository data without direct human-participant interaction.
- Ethics approval was not applicable because the study analyzed publicly available repository data without direct interaction with human participants.