NASA’s software discipline, crucial across Mission Directorates, emphasizes improving software engineering and automation risk management, adopting AI/ML innovations, and leveraging the Code Analysis Pipeline for software quality. Credit: SciTechDaily.comMission Directorates. Some recent discipline focus and development areas are highlighted below, along with a look at the Software Technical Discipline Team’s approach to evolving discipline best practices toward the future.
Some key findings shown in the above charts, indicate that software more often does the wrong thing rather than just crash. Rebooting was found to be ineffective when software behaves erroneously. Unexpected behavior was mostly attributed to the code or logic itself, and about half of those instances were the result of missing software—software not present due to unanticipated situations or missing requirements.
Examples of how NASA uses AI/ML. Satellite images of clouds with estimation of cloud thickness and wildfire detection . Credit: NASA