[Spike] [MVP] Package maintenance predictive model #444
Labels
kind/feature
Categorizes issue or PR as related to a new feature.
needs-triage
Indicates an issue or PR lacks a `triage/...` label and requires one.
priority/important-longterm
Important over the long term, but may not be staffed and/or may need multiple releases to complete.
sig/stack-guidance
Categorizes an issue or PR as relevant to SIG Stack Guidance.
Projects
Problem statement
cc @goern
As Python developer, I would like to be able to predict if some of my dependencies will go unmaintained with time.
The idea would be to develop a learning model able when a given package will go under an acceptable level of maintenance that could be defined by the user or directly in the model, in an arbitrary way.
A PoC for this model could use project maintenance data as provided by the OpenSSF Security Scorecards, given that the upstream project implements Scorecard checks per package version instead of updating Scorecards check given the project repository last commit SHA.
Proposal description
Think about ways to provide this model as a service, and where in a Python project lifecycle it would be most relevant for developers to predict the maintenance duration of their dependencies.
Acceptance Criteria
To be defined.
The text was updated successfully, but these errors were encountered: