Master Thesis: AI-Based Automated Test Data Analysis and Report Generation Tool

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About this opportunity:

In product verification and validation, large amounts of test data are generated from laboratory measurements, automated test systems, and network equipment. This data often consists of raw numerical values, text logs, and image-based results that require significant manual effort to analyse, visualize, and document in test reports.

The goal of this thesis is to investigate and develop a software tool that automatically transforms raw test outputs into meaningful insights, including statistical analyses, graphical visualizations, and automated report population.

The tool should be able to store and retrieve data from a database and classify the data based on the DUT vendor and run comparison between different DUT from different vendors in terms of performance parameters.

The solution should reduce manual effort, improve reporting accuracy, and accelerate the overall test verification workflow.

What you will do:

• Analyse existing test data formats including numerical measurements, textual logs, and image-based outputs.


• Design and develop a software application for automated test data processing.


• Convert raw measurement data into meaningful visualizations such as graphs, trend analyses, and statistical summaries.


• Investigate methods for extracting relevant information from text files and test result images.


• Implement automatic population of predefined test report templates and result tables.


• Evaluate the accuracy, efficiency, and usability of the developed solution.


• Demonstrate the tool using real-world test data from Ericsson verification environments.


• Present findings and recommendations for future deployment and enhancements.

The skills you bring:

• We are looking for students pursuing a Master’s degree in Computer Science, Software Engineering, Data Science or Artificial Intelligence.


• Strong programming skills in Python, C#, Java, or similar languages.


• Knowledge of data analysis and visualization libraries (e.g., Pandas, Matplotlib, Plotly).


• Understanding of statistics and data processing techniques.


• Familiarity with machine learning or AI concepts is considered a plus.


• Interest in automation, test engineering, and data-driven decision making.


• Ability to work both independently and collaboratively in a research and development environment.


• Knowledge about Optics, Electrical Engineering or a related field is a merit.