VLDB 2026 Research / reviewers in the wild / expert
Jill Marley
dblp:419/7428
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › software dependencies
software dependency management |
0.9 | 1 | 2025 | Which Is Better For Reducing Outdated and Vulnerable Dependencies: Pinning or Floatingƒ · ASE 2025 |
Methods — techniques the papers use, named apart from their topics
survival analysis · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Which Is Better For Reducing Outdated and Vulnerable Dependencies: Pinning or FloatingƒabstractDevelopers consistently use version constraints to specify acceptable versions of the dependencies for their project. Pinning dependencies can reduce the likelihood of breaking changes, but comes with a cost of manually managing the replacement of outdated and vulnerable dependencies. On the other hand, floating can be used to automatically get bug fixes and security fixes, but comes with the risk of breaking changes. Security practitioners advocate pinning dependencies to prevent against software supply chain attacks, e.g., malicious package updates. However, since pinning is the tightest version constraint, pinning is the most likely to result in outdated dependencies. Nevertheless, how the likelihood of becoming outdated or vulnerable dependencies changes across version constraint types is unknown. The goal of this study is to aid developers in making an informed dependency version constraint choice by empirically evaluating the likelihood of dependencies becoming outdated or vulnerable across version constraint types at scale. In this study, we first identify the trends in dependency version constraint usage and the patterns of version constraint type changes made by developers in the npm, PyPI, and Cargo ecosystems. We then modeled the dependency state transitions using survival analysis and estimated how the likelihood of becoming outdated or vulnerable changes when using pinning as opposed to the rest of the version constraint types. We observe that among outdated and vulnerable dependencies, the most commonly used version constraint type is floating-minor, with pinning being the next most common. We also find that floating-major is the least likely to result in outdated and floating-minor is the least likely to result in vulnerable dependencies. Based on our findings, we recommend that developers use any kind of floating constraint with lockfiles to balance the tradeoffs of pinning and floating. Imranur Rahman, Jill Marley, William Enck, Laurie A. Williams |
ASE | 2 |