Master Thesis: Open-Source Vetting and FOSS Introduction Analysis
publicerat av Ericsson
- Företag
- Ericsson
- Ort
- Stockholm
- Sista ansökningsdag
- Ej angiven
- Nivå
- Master/civilingenjör (30 hp)
- Passar program
- Computer Science, Software Engineering, Data Science, Statistics
Beskrivning
Ericsson uses free and open-source software (FOSS) in its software products, making reliable information about components essential for safe and responsible use. This thesis explores ways to improve FOSS metadata and establish dependable reference data for component vetting and introduction analysis. It will compare statistical, graph-based, machine-learning and AI-assisted approaches while keeping uncertainty visible and retaining expert oversight.
The assignment
- Design a metadata model for FOSS components and define measurable criteria for accuracy, completeness, consistency, currency and traceability.
- Examine representative data for errors, gaps, contradictions, duplicate entries and incorrect positive or negative findings.
- Explore techniques for standardizing component names and versions, matching records, mapping dependencies, tracing origins and assigning confidence scores.
- Develop a process for building and maintaining reference data that incorporates expert checks and ongoing updates.
- Implement a proof of concept and compare it with a baseline using precision, recall, coverage, confidence and the effort required for review.
- Recommend improvements to automated FOSS assessment and secure, compliant software supply chains.
Who we are looking for
- Currently studying for a master's degree in computer science, software engineering, data science, statistics or a related discipline.
- Interested in data quality, analytics, statistics, machine learning, software supply-chain security or open-source software.
- Keen to evaluate methods empirically and explore how trustworthy data supports explainable and auditable decisions.
- Experience with Python, SQL, graph data, package ecosystems, Git, CI/CD or cloud-native software is advantageous but optional.
- Able to work analytically and systematically, collaborate towards a research goal and take responsibility for individual contributions.
What we offer
- An opportunity to apply technical skills and creative thinking to challenging problems.
- Collaboration with a team focused on innovation and developing new solutions.
Practical details
Location: Stockholm. Recruitment reference: 792087.
Förkunskapskrav
Applicants should be pursuing a relevant master's degree and have an interest in reliable data, empirical evaluation and explainable decisions. An analytical, systematic approach and the ability to collaborate while owning individual contributions are expected. Experience with Python, SQL, graph data, package ecosystems, Git, CI/CD or cloud-native software is beneficial but not mandatory.
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