A LightGBM-XGBoost quantile regression model predicts CI build memory needs, delivering 36 GB average savings per build with under-allocation below 0.3% in production.
Practical Pipeline-Aware Regression Test Optimization for Continuous Integration
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Intelligent resource prediction for SAP HANA continuous integration build workloads
A LightGBM-XGBoost quantile regression model predicts CI build memory needs, delivering 36 GB average savings per build with under-allocation below 0.3% in production.