Bachelor and Master Theses

Title: Test Oracle Automation with Machine Learning: A Feasibility Study
Subject: Computer Science
Level: Advanced
Description: Test automation has been perceived by many companies as an effective way of reducing costs associated with software testing. This is even more emphasised in specific phases of software testing, namely regression testing, where re-testing of a system has to be conducted in order to ensure that previously working functionalities have not been corrupted with any of the additional features.
However, in order to have a fully functioning test automation, all aspects of software testing have to be automated including the test oracle, or the verdict, problem.

In this thesis, we will investigate to what extent it is feasible to utilise machine learning approach in deriving an automated oracle for its usage in regression testing phase. Two systems from Bombardier Transportation will be investigated: (i) Train Control Management System focusing mainly on digital signals as part of the verdict and (ii) Propulsion System having mostly analogue signals as part of the verdict process.
Company: Bombardier Transportation, kontaktperson: Ola Sellin
Prel. end date: 2018-06-15
Presentation date: 2018-06-01
Student: Nermin Imamovic
IDT supervisors:
Adnan Causevic, 021-101689
Examinator: Mobyen Uddin Ahmed
Mobyen Uddin Ahmed, +46-21-107369

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