Searching for high-fidelity builds using active learning
Harshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin · 2022
Modern software is incredibly complex. A typical application may comprise hundreds or thousands of reusable components. Automated package managers can help to maintain a consistent set of dependency versions, but ultimately the solvers in these systems rely on constraints generated by humans. At scale, small errors add up, and it becomes increasingly difficult to find high-fidelity configurations. We cannot test all configurations, because the space is combinatorial, so exhaustive exploration is infeasible.