On effective testing of health care simulation software

Abstract

Health care professionals rely on software to simulate anatomical and physiological elements of the human body for purposes of training, prototyping, and decision making. Software can also be used to simulate medical processes and protocols to measure cost effectiveness and resource utilization. Whereas much of the software engineering research into simulation software focuses on validation (determining that the simulation accurately models real-world activity), to date there has been little investigation into the testing of simulation software itself, that is, the ability to effectively search for errors in the implementation. This is particularly challenging because often there is no test oracle to indicate whether the results of the simulation are correct. In this paper, we present an approach to systematically testing simulation software in the absence of test oracles, and evaluate the effectiveness of the technique.

A Survey on Metamorphic Testing

“…The applicability of the approach was illustrated with a single metamorphic relation on a subject program with seeded faults. In later work, Murphy et al [75], [76] successfully applied SMT to the detection of faults in a health care simulation program with non-deterministic time events.…”

“…Based on their previous work [43], the authors used code coverage criteria to guide the selection of effective metamorphic relations and the creation of test cases. Murphy et al [76] proposed using metamorphic relations to systematically test health care simulation programs, and presented a case study with two real-world simulators and mutation testing. More recently, Núñez and Hierons [106] proposed using metamorphic relations to detect unexpected behaviour when simulating cloud provisioning and usage.…”

Predicting metamorphic relations for testing scientific software: a machine learning approach using graph kernels

“…Metamorphic testing has been used to test applications without oracles in different areas such as machine learning applications , healthcare simulations , Monte Carlo modelling , bioinformatics programmes , computer graphics , programmes with partial differential equations and variability analysis tools . Recently, metamorphic testing has been used to validate compilers and cloud models.…”

Using machine learning techniques to detect metamorphic relations for programs without test oracles

“…Xie et al used metamorphic testing to test machine learning applications [7]. Metamorphic testing was used to test simulation software such as health care simulations [29] and Monte Carlo modeling [30]. Metamorphic testing has been used effectively in bioinformatics [31], computer graphics [32] and for testing programs with partial differential equations [33].…”