The Machine Learning Automated Test Process (MALT-P) study is focused on investigating and prototyping the insertion of automation and machine learning methods in the domain of Automated Test Generation that can be used in both ESOC and ESTEC’s testing facilities.

The following tasks are proposed to accomplish the objectives of this activity:

• Analysis of relevant studies/literature and problem definition
• Use case selection and solution design
• Prototype implementation and evaluation
• Prototype validation and optimisation
• Lessons learned and way forward

NCSR-D will participate in MALT-P as a subcontractor of Etamax, and will lead the AI model prototype implementation and evaluation.