Input-Domain Software Testing for Failure Probability Estimation of Safety-Critical Applications in Consideration of Past Input Sequence
Author(s) -
Hee Eun Kim,
Han Seong Son,
Bo Gyung Kim,
Jaehyun Cho,
Sung Min Shin,
Hyun Gook Kang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2765698
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Software failure probability quantification is an important aspect of digital system reliability assessment. Several quantification methods currently available in the software reliability field have characteristics unsuitable for application to safety-critical software. In this paper, a software test framework in consideration of input trajectory is developed, and a software failure probability quantification method is also suggested. The test input cases consist of the states and present inputs, where input trajectory is represented by the state. To obtain the input domain, which represents realistic plant behavior, digital system characteristics and plant dynamics are considered. This allows software failure probability to be estimated by using the result of each representative test case, thus reducing testing efforts. The proposed framework was applied to a nuclear power plant reactor protection system as an example to show its effectiveness. The method provides a practical and relatively simple way to test software and estimate software failure probability.
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