Master Thesis: Crazy Tester - An Automated Test Approach Using ML hos IKEA Sweden


Testing code is an essential part of the software development life cycle but writing good test cases is not always trivial. As a developer it can be hard to estimate and predict user behavior and sometimes the test cases might be influenced by their own bias. In order to escape this, we would like to explore the possibility of having an automated test tool that can:

  • Create unbiased test cases

  • Explore edge cases in the code

  • Utilize machine learning

  • Document the taken action for future manual analysis

We would, for example, like to explore a use case where the test tool goes through all the links on a webpage in order to find dead links or some kind of unexpected behavior and document the action taken. This was how the crazy tester idea was born.


Our organization

The overall vision of our organization within IKEA, Customer Engagement, is to establish a customer data and marketing software foundation that enables a world-class, personalized meeting with the Customer.

The Customer Engagement area covers capabilities in areas such as Customer Information, Customer Analytics, Marketing and Loyalty. From a business software architecture perspective, the Customer Engagement area is quite complex since it consists of real time collaboration between global IKEA components and a large number of external partner components.

Customer Engagement is part of the “Reclaim IKEAs data and build new products in the cloud” initiative. In short - we are reclaiming our customer data - including all IKEA Family accounts - which has, up until now, often been managed by local vendors, and are building the capabilities to personalize the customer journey across IKEA touchpoints (digital and physical). Until now the majority of our components are built on GCP (Google Cloud Platform), but other cloud vendors are to be expected when rolling out software globally.



Investigate the possibility and success rate of an automated crazy tester that you will develop.

The main steps of the thesis shall be:

  • Do a literature study of best practices and research regarding E2E-tests and user behavior

  • Identify key metrics to evaluate the success

  • Implement a MVP (minimum-viable-product) crazy tester and evaluate in regards to the key metrics, possibly using machine learning

  • Get feedback from stakeholders

  • Improve and refine the crazy tester and integrate it with existing CI/CD pipelines


Scope: 2 students completing 30 credits (20 weeks) each

If you already have a partner in mind, apply individually and write your intended partner's name in the application.


If you have any questions

Please contact Pontus Jaensson on email:

Observera: De examensarbete och projekt som du hittar i SH Karriär är inte på förväg godkända av ditt universitet. Du måste själv se till att de eventuella samarbeten som du ingår med organisationer för examensarbete och projekt blir godkända av din handledare eller kursansvarig.