Finding Metamorphic Relations for Scientific Software

被引：7

作者：

Lin, Xuanyi ^{[1
]}

Peng, Zedong ^{[1
]}

Niu, Nan ^{[1
]}

Wang, Wentao ^{[2
]}

Liu, Hui ^{[3
]}

机构：

[1] Univ Cincinnati, Cincinnati, OH 45221 USA

[2] Oracle, Austin, TX USA

[3] Beijing Inst Technol, Beijing, Peoples R China

来源：

2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: COMPANION PROCEEDINGS (ICSE-COMPANION 2021) | 2021年

关键词：

Scientific software; metamorphic relation identification; Storm Water Management Model (SWMM);

D O I：

10.1109/ICSE-Companion52605.2021.00118

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Metamorphic testing uncovers defects by checking whether a relation holds among multiple software executions. These relations are known as metamorphic relations (MRs). For scientific software operating in a large multi-parameter input space, identifying MRs that determine the simultaneous changes among multiple variables is challenging. In this poster, we propose a fully automatic approach to classifying input and output variables from scientific software's user manual, mining these variables' associations from the user forum to generate MRs, and validating the MRs with existing regression tests. Preliminary results of our end-to-end MR support for the Storm Water Management Model (SWMM) are reported.

引用

页码：254 / 255

页数：2

共 9 条

[1]

[Anonymous], 2014, STORM WATER MANAGEME

[2] Coverage-based resampling: Building robust consolidated decision trees [J].