TY - GEN
T1 - A Framework for Standardized Partitioning Analysis in Integrated Modular Avionics Systems
AU - Zhang, Jilu
AU - Cai, Yong
AU - Miao, Weikai
AU - Wang, Zhouyang
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - With the increasing adoption of the Integrated Modular Avionics (IMA) architecture, ensuring robust partitioning, a fundamental technique of this architecture, is crucial. Additionally, the benefits of reduced verification costs that robust partitioning provides for software verification on multicore processor platform are undeniable. However, robust partitioning faces various challenges posed by the time partitioning and space/resource partitioning of shared and dedicated resources, which can compromise robust partitioning. Although DO-297 describes what a partitioning analysis should contain, there is still no systematic and complete guide available for organizing and addressing partitioning analysis activities in public research. We propose a systematic framework to guide the performance of specific tasks within partitioning analysis, including identifying top-level partitioning properties, decomposing these properties, extracting all potential error sources, combining potential error sources with robust partitioning properties to identify vulnerabilities and verifying mitigation means.
AB - With the increasing adoption of the Integrated Modular Avionics (IMA) architecture, ensuring robust partitioning, a fundamental technique of this architecture, is crucial. Additionally, the benefits of reduced verification costs that robust partitioning provides for software verification on multicore processor platform are undeniable. However, robust partitioning faces various challenges posed by the time partitioning and space/resource partitioning of shared and dedicated resources, which can compromise robust partitioning. Although DO-297 describes what a partitioning analysis should contain, there is still no systematic and complete guide available for organizing and addressing partitioning analysis activities in public research. We propose a systematic framework to guide the performance of specific tasks within partitioning analysis, including identifying top-level partitioning properties, decomposing these properties, extracting all potential error sources, combining potential error sources with robust partitioning properties to identify vulnerabilities and verifying mitigation means.
KW - multicore processor platform
KW - partitioning analysis
KW - space/resource partitioning
KW - time partitioning
UR - https://www.scopus.com/pages/publications/86000474378
U2 - 10.1007/978-981-96-1621-3_10
DO - 10.1007/978-981-96-1621-3_10
M3 - 会议稿件
AN - SCOPUS:86000474378
SN - 9789819616206
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 141
EP - 157
BT - Software Fault Prevention, Verification, and Validation - 1st International Symposium, SFPVV 2024, Proceedings
A2 - Liu, Shaoying
PB - Springer Science and Business Media Deutschland GmbH
T2 - 1st International Symposium on Software Fault Prevention, Verification, and Validation, SFPVV 2024
Y2 - 2 December 2024 through 3 December 2024
ER -