Improving the quality of scientific computing via software engineering methodologies

建议的研究计划的目的是提高科学计算（SC）软件的质量。 虽然已经实现了许多高质量的算法，特别是关于正确性，可靠性和性能的质量，还有其他质量，如可用性，可维护性，可验证性，生产力，可重用性和可移植性，往往被忽视。 为了解决这些质量问题，建议的方法是适应软件工程（SE）的方法，已成功地应用于其他类型的软件。 可以从SE中改编的一个新想法是将SC代码开发为程序族。 在这种方法中，类似的软件产品一起开发，重用公共部分，识别和系统处理可变功能。 这项研究有可能显着提高SC代码的可重用性，因为共同的代码只需要实现一次。 测试是SE实践的另一个领域，它将适应于提高SC软件质量的目标。 测试研究将是具有挑战性的，因为大多数测试方法假设，对于每一组测试输入的预期输出可以识别，但这往往不是SC软件的情况。 这一挑战将通过独立算法的并行测试技术来解决，与封闭形式的解决方案进行比较，使用区间和无限精度算法，后验误差估计和系统识别和记录解决方案的已知特性。

The objective of the proposed research program is to improve the quality of scientific computation (SC) software. Although many high quality algorithms have been implemented, especially with respect to the qualities of correctness, reliability and performance, there are other qualities, such as usability, maintainability, verifiability, productivity, reusability and portability that are often neglected. To address these quality concerns, the proposed approach is to adapt software engineering (SE) methodologies that have been successfully applied for other types of software. One new idea that can be adapted from SE is the development of SC code as a program family. In this approach similar software products are developed together, with the common parts reused and the variable features identified and systematically handled. This research has the potential to significantly improve SC code with respect to reusability because the common code only has to be implemented once. Testing is another area of SE practise that will be adapted with the goal of improving the quality of SC software. The testing research will be challenging because most testing methodologies assume that for each set of test inputs an expected output can be identified, but this is often not the case for SC software. This challenge will be addressed through techniques of parallel testing with independent algorithms, comparison to closed-form solutions, the use of interval and infinite precision arithmetic, a posteriori error estimation and systematic identification and documentation of known characteristics of the solution.