Prioritization and Perception of Quality Requirements in Decentralized Identity Applications

Quality requirements or non-functional requirements (NFR) are frequently described from the perspective of an organization that requires a software system to address a specific problem and achieve organizational goals. This approach is business-oriented and primarily reflects business goals. However, to design a user-centric system, the goals should be considered beyond the interests of a single organization and accurately reflect the perspective of users instead.

This thesis focuses on the use case of decentralized identity. It aims to prioritize qualities outlined by [1] from the perspective of the respective component (i.e., user, issuer, verifier) and understand whether respondents can connect a system functionality (or functional requirement (FR)) with a corresponding quality.

There are multiple goals in this thesis:

1. Assign existing quality requirements (specified by [1]) to a component of a decentralized identity system, namely user, issuer, and verifier. Briefly state the justification for why a quality requirement is categorized as such.
2. Identify who the representatives of each component are. Compose a comprehensive list of entities for each category.
3. Design three questionnaires for each user category. Each questionnaire should ask representatives of a category it is directed to (i) about their priority of each quality requirement (e.g., how important “privacy” is to you) and (ii) about their interpretation of whether a given functionality addresses corresponding quality (e.g., ability to select which information to share preserves privacy). Note, questionnaires should be accurately designed to ensure they are easy to understand to all types of users, do not have leading questions, and the order of questions do not impact how respondents answer. Additionally, depending on the identified representatives of each component, it might be necessary to design each questionnaire in both English and German languages.
4. Distribute questionnaires to the identified component representatives. This can be done via email or online posting (e.g., social media or university mailing list for regular user category).
5. Collect the data.
6. As the last step, analyse the data collected with each questionnaire using statistical analysis. This goal should answer two questions: (i) which qualities are important for each category of users and (ii) are the described functionalities and their mapping to quality requirements clear to the users. Create a visual prioritization matrix and compare the results with prioritization outlined by [1]. 

[1] Čučko, Š. Bećirović, A. Kamišalić, S. Mrdović, and M. Turkanović, ‘‘Towards the classification of self-sovereign identity properties,’’ IEEE access, vol. 10, pp. 88 306–88 329, 2022.