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csx-home>vol-01>issue-04>A method for automated regression test in scientific computing libraries: illustration with SPHinXsys
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
Bo Zhang
Chi Zhang
Xiangyu Hu
TUM School of Engineering and Design, Technical University of Munich,
85748 Garching, Germany
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
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
The development of computers has pushed scientific computing to become an indispensable part of many technologies and industries, such as in assessing climate change [2], designing new energy conductors [3], and imposes an ever-widening effect on better predicting and understanding the phenomena of nature and engineered systems. Following the definition of validation and verification of scientific computing claimed by William [4], scientific computing should always represent the real world and the conceptual model accurately. However, this is a challenging task due to the complex mathematical models and calculations, which often require changes to separate parts of the application and definitely increase the possibility of errors. Moreover, the development of scientific applications is a lasting work, and changes occur frequently due to different requirements and new features introduced. The applications should always produce trustworthy results and assure the application qualities with the help of validation and verification conducted alongside both application development and usage [5]. Implementing testing, including unit test, integration test, regression test, system test, etc., can provide concrete validation and verification procedures. Notwithstanding the fact that it has already been adopted in many IT software, scientific applications, especially some open-source libraries, find it difficult to perform those testing directly with traditional techniques. One main challenge is due to the characteristics of the scientific application, as it’s hard to find a test oracle to check if the program can gain the expected output when executing test cases [6, 7]. Another challenge arises from cultural differences between scientists and the software engineering community [6]. Many scientific applications are usually developed by small-group scientists, who may not be very familiar with accepted software engineering practices, and haven’t studied the developing process of their software in much detail [8], and therefore may overlook the impact of changes. Regression test stands a great chance to ensure the output validity of scientific applications under development. It is a re-testing activity, which refers to executing the test suite with given inputs and comparing the output with previously stored reference results when modifications occur or new features are added. In this way, developers can make sure that their changes don’t cause any unexpected side effects and previous functionalities are still verified [7]. Since taking the regression test for all test cases is generally
Conclusion
This paper introduces a method for developing an automatic regression test environment for open-source scientific libraries and uses SPHinXsys as an illustration to demonstrate its functionality. For scientific libraries under centralized development, it’s essential to guarantee the accuracy of simulation results all the time, and the regression test provides this procedure. The reference database for each benchmark test is generated using different strategies, and the new result after code modifications can be automatically tested with them once the source code is updated. This regression test environment has been implemented in all test cases released in SPHinXsys, and it shows great functionality to check the validity of the new result obtained after code modifications. By doing such work, we also want to draw some attention from general scientific computing communities to emphasize the software performance during development. The principle of the regression test proposed here is universal and can be applied and extended in other libraries and applications. In the future, other regression test methods will be implemented, and with the number of test cases swelling due to adding new dynamics features, selection and reduction of test cases will also be adopted.
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