Master Thesis: Requirements to Verified RTL Releases: A Multi-Agent Traceability Framework for ASIC

Technology, Data & Digital · Software & Web Development · Software Engineering · Embedded Systems · Artificial Intelligence

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In short

This Master Thesis project focuses on developing and testing a multi-agent ecosystem for feature-centric traceability and quality assurance in ASIC IP development. It aims to connect requirements with Jira work items, RTL revisions, documentation, and release baselines using AI and LLMs to improve XFT autonomy and release transparency.

Responsibilities

Develop and test a 'Multi-agent ecosystem for feature-centric traceability and internal + external releases quality assurance and quality gating in for a cross-functional teams-oriented Organization supporting agile ways of development a complex ASIC IP.
Ingest requirement specifications and connect them with Jira work items movement, RTL revisions for optimization or feature-changes, Documentation updates e.g. DS, VS, reference-model implementations, verification evidence, FPGA builds and release baselines.
Design specialized agents with clearly defined roles and a coordinating agent to construct an auditable artifact graph, perform change-impact analysis and generate explainable quality-marker reports.
Combine LLM-based semantic reasoning with deterministic version, dependency and quality-gate rules.
Evaluate the prototype using traceability accuracy, warning precision, evidence completeness, unsupported-claim rate and practitioner assessment.
Contribute a technically rigorous approach for improving XFT autonomy while preserving system-level consistency, release transparency and engineering accountability.

Requirements

Knowledge in Computer Science, Electrical Engineering, or a related field.
Experience in at least one programming language (Python not mandatory).
Eagerness to learn and explore new concepts.

Desired Qualifications

Curious mind
Bonus: experience in machine learning.

Benefits

Thesis work opportunity

Skills

PythonMachine Learning

#AI#ASIC#RTL#Requirements Engineering#Traceability#Quality Assurance#Agile#LLM#Python

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