  Correcting bugs using modern Automated Program Repair (APR) can be both
time-consuming and resource-expensive. We describe a program repair approach
that aims to improve the scalability of modern APR tools. The approach
leverages program reduction in the form of program slicing to eliminate code
irrelevant to fixing the bug, which improves the APR tool's overall
performance. We investigate slicing's impact on all three phases of the repair
process: fault localization, patch generation, and patch validation. Our
empirical exploration finds that the proposed approach, on average, enhances
the repair ability of the TBar APR tool, but we also discovered a few cases
where it was less successful. Specifically, on examples from the widely used
Defects4J dataset, we obtain a substantial reduction in median repair time,
which falls from 80 minutes to just under 18 minutes. We conclude that program
reduction can improve the performance of APR without degrading repair quality,
but this improvement is not universal.
  A replication package is available via Zenodo at
https://doi.org/10.5281/zenodo.13074333.
  Keywords: automated program repair, dynamic program slicing, fault
localization, test-suite reduction, hybrid techniques.
