Regular dependency updates protect dependent software components from upstream bugs, security vulnerabilities, and poor code quality. Measures of dependency updates across software ecosystems involve two key dimensions: the time span during which a release is being newly adopted (adoption lifespan) and the extent of adoption across the ecosystem (adoption reach). We examine correlations between adoption patterns in the Maven software ecosystem and two factors: the magnitude of code modifications (extent of modifications affecting the meaning or behavior of the code, henceforth called “semantic change”) in an upstream dependency and the relative maintenance rate of upstream packages. Using the Goblin Weaver framework, we find adoption latency in the Maven ecosystem follows a log-normal distribution while adoption reach exhibits an exponential decay distribution.

We examine how gender impacts the use of specific programming languages, as analyzed across a stratified sample of 100k unique software developers from the World of Code (WoC) archive. A total of 50,000 male and 50,000 female developers are identified using the name-to-gender inference tool WikiGender-Sort. The top fifteen programming languages according to the 2024 StackOverflow Developer survey are considered. For each developer, we count the number of files that are edited in each programming language and compute the median across gender categories. Men and women tend to edit the same number of files among most programming languages, with the exception of developers using C#, C, Go, and Rust, which had more edits among men.

An approach to automatically recover the name of the branch where a given commit is originally made within a GitHub repository is presented and evaluated. This is a difficult task because in Git, the commit object does not store the name of the branch when it is created. Here this is termed the commit's branch of origin. Developers typically use branches in Git to group sets of changes that are related by task or concern. The approach recovers the branch of origin only within the scope of a single repository. The recovery process first uses Git's default merge commit messages and then examines the relationships between neighboring commits. The evaluation includes a simulation, an empirical examination of 40 repositories of open-source systems, and a manual verification. The evaluations show that the average accuracy exceeds 97% of all commits and the average precision exceeds 80%.