Master Thesis: AI-driven Test Fault Classification
Ericsson ABNy
Sammanfattning
This opportunity involves a thesis project focused on optimizing software testing through automation at Ericsson in Linköping, Sweden. The role aims to reduce manual efforts in identifying and classifying faults in test cases, ultimately enhancing the debugging process and ticket creation. Candidates will work in a collaborative environment, leveraging their skills in software testing and AI/ML.Det här erbjuder vi
Opportunity to work on innovative solutions to complex problems.Collaborative and diverse team environment.Encouragement of diverse and inclusive work culture.
Ansök senast: Öppet tillsvidare
Publicerad: 2026-09-29
Beskrivning
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About this opportunity:
Following conventional software ways of working, a significant amount of manual work is necessary to determine the cause of any test case failure. These efforts can be broken down as follows:
These efforts may increase when the failure of a test is due to flakiness and makes no sense to the tester. Identifying the fault is one activity, but classifying it (fault of product, test, infrastructure, external library, etc.) and creating a trouble report / ticket are additional steps that add time and overhead before actually correcting the fault.
What you will do:
The purpose of this thesis is to optimize testing using automated ways to identify and classify faults. Automatic identification and classification of faults will reduce manual effort and provide a comprehensive database with common faults, thus saving debugging time and effort of analyzing logs or error messages. We would also like to investigate how to create automated tickets with necessary and consistent information about the fault. Availability of such consistent information (product, build id, component, team name, fault text etc.) will enhance ways of working towards the ticket/fault resolution.
The skills you bring:
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.
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 791418
About this opportunity:
Following conventional software ways of working, a significant amount of manual work is necessary to determine the cause of any test case failure. These efforts can be broken down as follows:
- Parsing test logs to determine why a failure occurred.
- Applying expert judgment and domain knowledge acquired over a longer period working with similar test suites or components.
- Engaging in discussions with colleagues who have encountered similar problems.
- Aggregating knowledge from historical data or similar failures.
These efforts may increase when the failure of a test is due to flakiness and makes no sense to the tester. Identifying the fault is one activity, but classifying it (fault of product, test, infrastructure, external library, etc.) and creating a trouble report / ticket are additional steps that add time and overhead before actually correcting the fault.
What you will do:
The purpose of this thesis is to optimize testing using automated ways to identify and classify faults. Automatic identification and classification of faults will reduce manual effort and provide a comprehensive database with common faults, thus saving debugging time and effort of analyzing logs or error messages. We would also like to investigate how to create automated tickets with necessary and consistent information about the fault. Availability of such consistent information (product, build id, component, team name, fault text etc.) will enhance ways of working towards the ticket/fault resolution.
The skills you bring:
- Master's student in computer science, computer engineering or similar.
- Background in software testing and AI/ML is preferred.
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.
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 791418
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Master Thesis: AI-driven Test Fault Classification
Ny
OM FÖRETAGET
Ericsson AB
