[School of Engineering PhD Scholarships] Filling the Gaps in AI Software Assurance through Exploratory Testing

About the project

About the Project AI can generate large software test suites from requirements, source code, specifications, examples and existing tests. However, these tests may reproduce the assumptions already embedded in their inputs. The result can be an illusion of comprehensive coverage while important questions about user goals, unexpected behaviour and system risks remain unexplored. This PhD will investigate how exploratory testing can provide a genuinely different source of software assurance. Rather than treating an exploratory session as a temporary activity that produces only bug reports, the project will develop ways to capture it as structured, reusable evidence, going beyond current capture-replay tools. A prototype “Exploratory Mode” will record the underlying interaction stream, allowing testers to attach observations and test outcomes to particular points in the stream. The project will investigate techniques for combining analysis of test results produced by CI servers and of exploratory tests undertaken by multiple testers on overlapping aspects of functionality. Differential exploratory testing techniques will allow tests to be run against multiple software versions simultaneously, allowing behavioural differences to be highlighted automatically and linked directly to tester observations. We will examine whether these methods can reveal “coverage illusions” and systematic blind spots in test results from AI generated and legacy test suites. The project will combine software-tool development with empirical evaluation through controlled studies, case studies and representative software systems. The project would suit a candidate interested in methods for analysing the trustworthiness of AI generated software, and in the combination of human factors and software testing research. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships . If you don’t already have an applicant account, please follow the instructions here. . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree (or international equivalent) in Computer Science, Software Engineering, Artificial Intelligence, HCI or a cognate discipline OR any upper-second class (2:1) honours degree and a Master’s degree at merit (or international equivalent) in Computer Science, Software Engineering, Artificial Intelligence, HCI or a cognate discipline (or international equivalent). Strong programming ability is essential. Experience in software engineering will be an advantage. This project will remain open until filled. If your application is submitted by 1 st November 2026, you can expect a decision by 18 th December 2026. If your application is submitted by 15 th January 2027, you can expect a decision by 30 th March 2027. Self or externally funded students can also be considered for this project. FSESoE

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