In today’s centralized identity systems, large companies control and store user datain a centralized manner, which poses a risk to users’ privacy and personal data. Self-sovereign identity (SSI) decentralizes digital identity management and gives individu-als full control over which personal data is shared and with whom. Furthermore, SSIenables verifiable credentials, allowing companies, authorities and individuals to buildnetworks of trust among themselves. This thesis discusses SSI, as well as a project whereSSI is practically applied in a mobile software application project for the distribution ofdigital drink tickets. The goal of the project is to develop a prototype to demonstratehow SSI can be applied in a general application, that involves issuing a verifiable cre-dential in the form of a drink ticket. To realize the project goal, an application has beendeveloped in React Native, where several frameworks for SSI have been studied. ”AriesCloud Agent Python” (ACA-Py) has been integrated with a REST API to provide SSIfunctionality to the project. The project has resulted in a working mobile applicationthat can issue and verify digital drink tickets, stored in the digital wallet application ofthe ticket holder. Minimal personal data is shared with the application, and only withthe exclusive approval of the ticket holder. The result confirms the potential of SSI fordecentralized identity management. / I dagens centraliserade identitetssystem är det stora teknikföretag som lagrar och kon-trollerar användardata, vilket medför en risk för användarnas integritet och personligadata. ”Self-sovereign identity” (SSI) decentraliserar digitala identiteter och ger indivi-den full kontroll över vilka personliga data som delas och till vem. Vidare möjliggörSSI verifierbara legitimationer, där förtroendenätverk byggs mellan företag, myndig-heter och individer. Denna uppsats avhandlar SSI, samt ett projekt där SSI appliceratspraktiskt i en mobilapplikation för distribution av digitala dryckesbiljetter. Målet medprojektet är att utveckla en prototyp för att visa hur SSI kan appliceras på en generellapplikation som innebär utgivande av en verifierbar legitimation i form av en dryckesbil-jett. För att realisera målet har en applikation utvecklats i React Native, där flera ramverkför SSI har studerats. ”Aries Cloud Agent Python” (ACA-Py) har integrerats genomREST API för att tillhandahålla SSI-funktionalitet till projektet. Projektet har resulterati en fungerande mobilapplikation som kan utfärda och verifiera digitala dryckesbiljetter,som lagras på en biljettinnehavares digitala plånboksapplikation. Minimal personligdata delas med mobilapplikationen och med innehavarens exklusiva tillstånd. Resultatetbekräftar potentialen av SSI för decentraliserad digital identitetshantering.

Advancements within Large Language Models(LLMs) have opened a world of opportunities within the software development domain. This thesis, through an controlled experiment, aims to investigate how LLMs can be utilized within software testing, more specifically unit testing. The controlled experiment was performed using a Python script interfacing with the gpt-3.5-turbo model, to automatically generate unit tests for React Native components written in TypeScript. The pipeline described, performs the calls to the OpenAI Application Programming Interface(API) iterative. To evaluate and retrieve the metric code coverage, the unit tests were executed with Jest. Additionally, manual execution of failing tests, both compilable and non-compilable tests were executed and the different kind of errors with their frequency were documented. The experiment shows that LLMs can be used to generate comprehensive and accurate unit tests, with high potential of future improvements. While the amount of generated tests that compiled were low, their nature was often good, failing because of easy correctable syntax errors, faulty imports or missing dependencies. The errors found, were at large part due to project configurations while others would probably be less frequent through more extensive prompt-engineering or by the use of an newer model. The experiment also shows that the temperature affected the outcome and that the type of errors were different between compiling and non-compiling tests. A lower temperature parameter to the OpenAI API generally achieved better results, whilst a higher temperature showed greater coverage at compiled failing tests. This thesis also shows that future opportunities and improvements are widely available. Through better project optimization, newer models and better prompting, a better result is to be expected. The script could with further development be turned into a working product, making software testing faster and more efficient, saving both time and money while simultaneously improving the test case quality.

The diploma thesis deals with design and implementation of the information system for sale support. In the first part of the thesis is done market analysis and described legislative requirements. These theoretical findings are further applied in the design part of the system. System is designed in spirit of good user experience(UX). Application is created with offline-first approach by React Native framework for cross-platform development of mobile applications. Synchronization between end point devices is done by CouchDB database system.