Using package managers is a simple and common method for reusing code through project dependencies. However, these, direct, dependencies can themselves rely on additional packages, resulting in indirect dependencies. It may then become complex to get a grasp of the whole set of dependencies of a project. Beyond studying individual projects, a deep understanding of software ecosystems is also a critical prerequisite for achieving sustained success in software development. This paper presents the 2025 edition of the MSR conference mining challenge. This year’s mining challenge focuses on dependencies and dependency ecosystem analysis using the Goblin framework that has been presented at the previous edition of the MSR conference. Goblin is composed of a Neo4j Maven Central dependency graph and a tool called Weaver for on-demand metric weaving into dependency graphs. As a whole, Goblin is a customizable framework for ecosystem and dependency analysis.

Keeping dependencies up to date is a crucial software maintenance task that requires significant effort. Developers must choose which dependencies to update, select appropriate target versions, and minimize the impact of updates in terms of breaking changes and incompatibilities. Several factors influence the choice of a new dependency version, including its freshness, popularity, absence of vulnerabilities, and compatibility.

Dependency graphs support software maintenance and software ecosystem analysis. Several metrics can be used on top of these graph models but the set of such metrics is to evolve over time. Further, some metrics have a dynamic nature, requiring being able to "rewind" dependency graphs at some point in time. To address these issues we propose the Goblin framework. It is composed of a dependency graph metamodel with time-related information, a miner to retrieve the graph from Maven Central, and a tool for on-demand metric weaving into dependency graphs. As a whole, Goblin is a customizable framework for ecosystem and dependency analysis. This is illustrated with a set of complementary experiments. Our tools, datasets, and experiments are freely available online.