Master Thesis - Generative AI Test Chain

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About this opportunity

When working with large scale soft ware development it is common to have a test chain before committing the product delivery. A common concept is to try to test as much as possible at an early as possible in the test chain and leave the more time consuming and expensive testing to the later stages in the test chain. Some of the previously dominant ways of thinking around test chains are now revisited as generative AI tools and agentic approaches are making its way into the software development flows. This master thesis project intends to look broadly on methods for designing, implementing, executing, assessing, automating and deploying test cases for quality assurance.

What you will do

This Master Thesis aims to investigate the current ways of working and the tools supporting it and compare that with what it might potentially be.

You will have freedom to define areas of exploration within the project. These could include, but are not limited to:

Creating or improving tooling to optimize the flow of testing.

Create a best-in-class scenario from a theoretical perspective studying what others have done.

Deep dive into one of the tools or phases to study that in detail

Investigate return of investment for any suggested changes

The skills you bring

Currently pursuing a Msc in Computer Science, Electrical Engineering, or a related field.

Experience in at least one programming language

Eagerness to learn and explore new concepts.

Bonus: experience in Generative AI and telecom

Why join Ericsson?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

Primary country and city: Sweden (SE) || Lund

Req ID: 792233