Trial lecture
Search-Based Software Testing: Fundamentals and Emerging Trends”
Time and place: September 1, 2026 11:15 AM. Kristen Nygaards sal (5370), Ole-Johan Dahls hus.
Main research findings
Quantum computing promises to tackle problems that are difficult for today’s classical computers, with potential applications in medicine, chemistry, and materials science. However, current quantum computers are sensitive to quantum noise which effects the results of a computation and limits its potential.
Quantum noise also makes testing quantum software difficult. Unlike ordinary programs, quantum programs can produce probabilistic results, and their internal states cannot simply be inspected without changing them. Traditional software testing methods therefore need to be redesigned. Even worse, when a test fails on a real quantum computer, it can be unclear whether the problem is a software bug or simply hardware noise.
This thesis explores ways to make quantum software testing practical on noisy, real-world machines. It uses machine learning to learn patterns of hardware and program specific noise and reduce its effects during testing. The work introduces methods to adapt existing testing approaches to work on noisy quantum computers. Such methods are designed to work across different quantum computers and programs.
The thesis also develops new testing approaches, which generate and evaluate tests while explicitly considering noise. Together, these techniques move quantum software testing closer to reliable, scalable testing on real hardware.
Adjudication committee
- Professor Andrea De Lucia, University of Salerno, Italy
- Dr. Gunel Jahangirova, King’s College London, UK
- Professor Amirhosein Taherkordi, University of Oslo, Norway
Supervisors
Professor Shaukat Ali, Simula, Norway
Professor Tor Skeie, University of Oslo, Norway
Associate Professor Paolo Arcaini, National Institute of Informatics, Japan
Chair of defence
Professor Özgu Mira Alay-Erduran
Contact information at Department: Pernille Adine Nordby