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Master Thesis: Beyond Git: Source Control Architecture for Agentic Software Development

Ericsson

Описание

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About this opportunity

Investigate how conventional Git-based source control behaves when hundreds of autonomous AI coding agents work concurrently on a shared codebase, and compare it with alternative architectures for agent-scale development. Build an experimental environment simulating up to approximately 500 concurrent agents and evaluate scalability, merge behavior, CI impact, resource consumption and semantic integration failures.

Обязанности

AI coding agents are quickly moving from assisting individual developers to working autonomously and in parallel on the same codebase. Git and the CI pipelines built around it were designed for a small number of human contributors, not hundreds of agents committing, branching and merging at machine speed. This Master Thesis investigates where that model breaks down, and which alternative architectures handle agent-scale development better.

You are encouraged to research similar solutions at other large scale software companies. You will have freedom to define areas of exploration within the project. These could include, but are not limited to:

o Designing realistic agent workloads and task distributions.
o Defining a reproducible setup for running and scaling the simulations.
o Selecting representative codebases of different sizes and levels of modularity.

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