AI/ML for Safety-Critical Software: The Case of the Space Domain

被引：0
作者：
Petrucci, Alberto [1 ,2 ]
Basciani, Francesco [3 ]
Pelliccione, Patrizio [3 ]
机构：
[1] Gran Sasso Sci Inst, I-67100 Laquila, Italy
[2] Thales Alenia Space, Cannes, France
[3] Gran Sasso Sci Inst, Comp Sci, I-67100 Laquila, Italy
来源：
IEEE SOFTWARE | 2025年 / 42卷 / 03期
关键词：
Testing; Qualifications; Standards; Documentation; Software safety; Software reliability; Quality assurance; Artificial intelligence; Machine learning;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
We analyze the current way of producing safety-critical software and the reference safety and assurance standards in the domain of spacecraft, namely, ECSS-Q-ST-80C and ECSS-E-ST-40. Then, we explore the readiness of correct practices to ensure that machine learning- or AI-enabled systems are safe and reliable.
引用
收藏
页码：107 / 114
页数：8
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