Master Thesis: AI-Assisted Verification and Data-Driven Migration for Ericsson Common Test System

Stack

Responsibilities

• ▹Design and evaluate an automated framework for comparing legacy NGTE/RVC implementations with CTS implementations
• ▹Execute equivalent test scenarios and automatically compare outputs and behavior
• ▹Detect and classify differences, distinguishing expected variations from potential defects
• ▹Explore AI-assisted techniques for anomaly detection, pattern recognition and result classification
• ▹Develop a confidence-scoring approach for assessing migration readiness
• ▹Create data-driven methods to prioritize migration candidates based on risk, complexity, dependencies and business value
• ▹Measure migration progress, identify rollout risks and bottlenecks, and provide actionable insights to stakeholders
• ▹Explore dashboard visualization and CI/CD integration concepts for continuous validation
• ▹Evaluate the proposed solutions using relevant Ericsson migration data and provide recommendations for future CTS rollout and migration planning

Requirements

• ▹Pursuing an MSc degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Systems or a related field
• ▹Strong programming skills in Python and/or Java
• ▹Interest in software testing, verification, test automation and software quality engineering
• ▹Knowledge of CI/CD, DevOps, data analytics and/or machine learning
• ▹Interest in dashboard development, data visualization and turning complex data into actionable insights

Nice to have

• ▹Knowledge of migration planning, anomaly detection or continuous validation

Soft skills