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Background
The test automation for our Android ECU today is done using indigenously developed python framework based on google test framework (uiautomator) and pytest.
Problem
- Today test development is not happening in parallel with software development.
- The test development is tightly connected to the software development and the test is more prone to break due to non-functional software changes. This also demands more time for maintenance of the tests.
- Not capable of giving on-demand feedback for the developers
- Questions stability of the test
Solution
Investigate different android testing framework on the market and present the Pros and Cons of different framework and its adaptability to our Android based ECU.
Focus may include the topics below:
- Pre-build tests using AI (Artificial Intelligence)
- Seamless algorithmic locators' system
- Auto test maintenance
- Capability to integrate into CI (Continuous Integration)
- Pricing plan
- Licensing terms
Goal of the thesis
Submission of a detailed study report by analyzing the pros and cons of different android test frameworks and their adaptability to our Android based ECU.
Desirable expertise
- Embedded systems
- Automotive systems
- Linux, Python
- Artificial Intelligence
- Machine Learning
- Android
- CI/CD
Kick-off date
Any time in 2022 or beginning of 2023
Additional info
The scope can be flexible and adapted to 1-2 students, depending on how many students you are and how much time you have for your thesis
Some reference links:
- https://www.tensorflow.org/
- https://huggingface.co/
- https://learntodroid.com/android-testing-tools/
- https://www.softwaretestinghelp.com/5-best-automation-tools-for-testing-android-applications/#1_21_8211_AI_Test_Creation_And_Analytics_For_Android
Tutor
Annamalai Vellaichamy, Product Manager