Thesis: Verification Machine Learning

Finding early issues in Embedded Development using Artificial Intelligence
Background
The increasingly complex embedded systems are being tested, integrated and released continuously. The Continuous Delivery Platform provides an automated pipeline from Code to Release. It is critical to make sure that the software released is of the highest grade and tested thoroughly.
Problem
New code changes are being generated continuously, with demand for an agile development they shall be released in an on-demand fashion while still making sure it’s of the highest quality and working as expected. It’s usually hard to foresee the actual end usage - even with several hundred different test cases. While we put the unit under heavy testing there can still be issues that are left unnoticed and can cost severe damage.
Solution
With the current infrastructure we generate huge amount of data from testing, most of which is not used unless they provide a clear exception.
With the help of artificial intelligence we see benefit of understanding a broader state of the testing and how they change over time. Being able to generate new testing solutions that can increase the quality for our customers.
Goal of the thesis
Create Service(s) that can be a foundation for how Volvo verifies upcoming releases of embedded devices. Understand patterns from to live feed together with historical data. And, if needed, generate additional testing that can put the verification on a new level.
Desirable expertise
  • Python
  • Micro services
  • SQL
  • Distributed messaging systems
  • TensorFlow or other machine learning libraries
Kick-off date
2020
Additional info
No special licenses or equipment is needed. Code is written with free and/or Open Source Software.
Thesis supervisors: Samuel Genheden and Henrik Nilsson.
Since the data is stored inside Volvo it’s mandatory that the tests are done inside Volvo Network as well. Some data may or will be classified. Code can be written in “Offline” Fashion on your local data with data that can be taken outside the Volvo System. But needs to be approved to not include confidential data.
For more information please contact
Gabriel Ibáñez, Innovation Leader, 0722388479

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