Master Thesis: Evaluating AI-Generated Alternatives to Open-Source Dependencies

Technology, Data & Digital · Software & Web Development · Software Engineering · Cybersecurity · Machine Learning

In short

This Master's thesis investigates whether AI-generated code can replace third-party open-source dependencies in software development. The project involves defining evaluation criteria, building a toolchain for AI implementation and comparison, and evaluating correctness and security to create a decision framework for responsible AI code replacement.

Responsibilities

Survey research on AI code generation and dependency management.
Define how a generated replacement should be judged against the original library.
Build a toolchain to extract a library's public interface, have an AI agent implement a replacement, and compare the results.
Evaluate correctness, security (including vulnerability history), and other relevant qualities.
Develop a decision framework indicating when AI-generated code replacement is a responsible choice.
Present findings to the Ericsson team.

Requirements

Master’s student in computer science, software engineering, cybersecurity, or related field.
Strong background in programming.
Experience with software testing and static analysis (preferred).
Familiarity with AI/LLM tooling (useful but not required).

Benefits

Outstanding opportunity to use your skills and imagination.
Chance to build solutions never seen before.
Be challenged in a team of diverse innovators.
Opportunity to craft what comes next.
Encouraging a diverse and inclusive organization.
Championing diversity in everything we do.
Collaborating with people with different experiences drives innovation.
Encouraging people from all backgrounds to apply.
Realize your full potential as part of the Ericsson team.

Skills

Artificial IntelligenceAlgorithmsAPIC++Academic WritingAgileArchitectureAnalyticsAmazon Web Services (AWS)

#Software & Web Development#Data, AI & Analytics#IT Infrastructure & Security

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