Making Root Cause Analysis Feasible for Large Code Bases
Author:
Affiliation:
1. University of Colorado Boulder, Boulder, CO, USA
2. National Center for Atmospheric Research, Boulder, CO, USA
3. Colorado School of Mines, Golden, CO, USA
Funder
Intel Parallel Computing Center for Weather and Climate Simulation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3307681.3325399
Reference37 articles.
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4. A. H. Baker Y. Hu D. M. Hammerling Y.-H. Tseng H. Xu X. Huang F. O. Bryan and G. Yang. 2016. Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0). Geo scientific Model Development 9 7 (2016) 2391--2406. A. H. Baker Y. Hu D. M. Hammerling Y.-H. Tseng H. Xu X. Huang F. O. Bryan and G. Yang. 2016. Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0). Geo scientific Model Development 9 7 (2016) 2391--2406.
5. Quality Assurance and Error Identification for the Community Earth System Model
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