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csx-home>vol-01>issue-04>A method for automated regression test in scientific computing libraries: illustration with SPHinXsys

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PTL PREMIUM

Submitted    10 March 2023

Revised          12 April 2023

Accepted       23 April 2023

A method for automated regression test in scientific computing libraries: illustration with SPHinXsys

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Bo Zhang

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Chi Zhang

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Xiangyu Hu

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TUM School of Engineering and Design, Technical University of Munich,
85748 Garching, Germany

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Canadian Science Letters X

2023 ° 13(05) ° 01-04

https://www.wikipt.org/csx-home

DOI: 10.1490/69802.105csx

Acknowledgments


The first author would like to acknowledge the financial support provided by the China Scholarship Council (No.202006230071). C. Zhang and

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Abstract

Scientific computing libraries, either in-house or open-source, have experienced enormous progress in both engineering and scientific research. It is therefore essential to ensure that the modifications in the source code aroused by bug fixing or new feature development wouldn’t compromise the accuracy and functionality that has already been validated and verified. With this in mind, this paper introduces a method for developing and implementing an automatic regression test environment and takes the open-source multiphysics library SPHinXsys [1] as an example. Firstly, the reference database for each benchmark test is generated from monitored data by multiple executions. This database contains the maximum variation range of metrics for different types of strategies, i.e., time-averaged method, ensemble-averaged method as well as the dynamic time warping method, covering the uncertainty arising from parallel computing, particle relaxation, physical instabilities, etc. Then, new results obtained after source code modification will be tested with them according to a curve-similarity-based comparison. Whenever the source code is updated, the regression test will be carried out automatically for all test cases and used to report the validity of the current results. This regression test environment has already been implemented in all dynamics test cases released in SPHinXsys, including fluid dynamics, solid mechanics, fluid-structure interaction, thermal and mass diffusion, reaction-diffusion, and their multi-physics coupling, and shows good capability for testing various problems. It’s worth noting that while the present test environment is built and implemented for a specific scientific computing library, its underlying principle is generic and can be applied to many others. Keywords: Scientific computing, Open-source library, Verification and validation, Regression test, Automatic test environment, Curve similarity comparison, Smoothed particle hydrodynamics.

Introduction