About this role
Build an AI-Assisted Release Health Monitor for the DDU ECU The opportunity How can software teams see whether a vehicle ECU is ready for release when important information is spread across different tools and teams? In this thesis, you will explore that challenge by designing and building a prototype release health monitor for the DDU ECU. You’ll bring together selected release, quality, safety, and cybersecurity information in a dashboard that helps teams understand readiness, spot gaps, and make better-informed decisions. The prototype will support human decision-making; it will not make release decisions. You’ll work with relevant stakeholders to understand their needs, select useful indicators, and evaluate whether the solution provides a clear and trustworthy overview.
- What you’ll work on Explore how DDU release, quality, safety, and cybersecurity information is created and managed.
- Identify the indicators that are most useful for understanding release readiness.
- Design a common information model for status, risks, blockers, actions, evidence, ownership, and data freshness.
- Build a prototype dashboard connected to selected, approved data sources.
- Create useful views for stakeholders such as product owners, system owners, safety and cybersecurity roles, and developers.
- Identify patterns or highlight anomalies in selected release data.
- Evaluate the prototype with representative users and recommend how it could be developed further.
- What you’ll deliver A working prototype dashboard for DDU release health monitoring.
- An information model describing the selected indicators and their sources, owners, and update frequency.
- Dashboard views covering release readiness, quality, risks, blockers, actions, and safety and cybersecurity status.
- An evaluation of the prototype’s usability, information quality, traceability, and usefulness.
- Recommendations for future development, governance, security, and integration.
- Who should apply This thesis is suited to students pursuing a master’s degree in Computer Science, Software Engineering, or Computer Engineering.
- You should enjoy software development and working with data from different sources.
- Experience or interest in dashboards, data integration, AI, embedded systems, automotive software, safety, or cybersecurity would be valuable.
Contact persons and supervisors Linda Sandberg, Unit manager, [email protected] Reyhaneh Ezatpanah, Thesis supervisor, [email protected] Application: Your application must include a CV, personal letter and transcript of grades A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.