Master Thesis: Reducing Test Flakiness with AI

Technology, Data & Digital · Software & Web Development · Software Engineering · Data Science

In short

This Master Thesis project at Ericsson in Linköping, Sweden, focuses on reducing and eliminating test flakiness using AI/ML. You will develop a proof-of-concept to detect, predict, and decrease flaky tests, collaborating with an investigated team. This is an excellent opportunity for a Master's student in computer science or computer engineering to contribute to improving software testing quality and developer productivity.

Responsibilities

Limit the scope of the study by investigating whether the test flakiness is due to production code, testing code, or testing infrastructure.
Develop a proof-of-concept implementation of state-of-art algorithms (using AI/ML, if needed) to detect, predict, and decrease test flakiness in collaboration with the investigated team.

Requirements

Master´s student in computer science, computer engineering or similar.
Background in software testing and AI/ML is preferred.

Benefits

Outstanding opportunity to use skills and imagination to push the boundaries of what's possible.
Build solutions never seen before to some of the world’s toughest problems.
Be challenged, but not alone, joining a team of diverse innovators.

Skills

Artificial IntelligenceMachine LearningAlgorithmsSoftware TestingAnalysis

#Master Thesis#AI#Machine Learning#Software Testing#Flaky Tests#Root Cause Analysis#Test Detection#Test Prediction#Computer Science#Computer Engineering

About Ericsson

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