Mobile Testing Framework Exploiting Machine Learning and NLP
Research Groups GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Thesis type EXPERIMENTAL
Description Thanks to the recent developments in Natural Language Processing and Machine Learning algorithms, it is the perfect time to apply these technologies in support of human software testers to make their work less cumbersome and improve efficiency in test deployment.
During this research thesis, you will have to develop and improve a testing framework for mobile Android applications that will be able to classify android apk and activities to suggest the best choice among already developed tests from a test suite. The candidate will have to develop as long as the framework evolves, new software tests. It is important to consider the human in the loop in the context of test development meanwhile ML and NLP as a support for the human and not a replacement.
This platform has to be a usable testing framework that collaborates with Python-based Machine Learning algorithms. The candidate will use testing frameworks such as Espresso and Appium. The candidate is also required to implement machine learning algorithms, with the exploratory possibility of deep learning using popular frameworks (PyTorch, TensorFlow, Keras, etc.) and also with state-of-the-art approaches like (Transformer based Encoders, Deep Neural Network, etc.).
Required skills Corso Mobile Application Development
Conoscenza base di Python (ML e NLP)
Conoscenza base di testing per applicazioni mobili
DisponibilitÓ a partecipare in un gruppo di ricerca
Skill di problem solving
Deadline 02/09/2021 PROPONI LA TUA CANDIDATURA