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Organisatsiooni nimi

Software Engineering Analytics

Kokkuvõte

While Large Language Models (LLMs) transform how code is generated, their environmental impact remains unexplored. This thesis dives into the energy efficiency of LLM-generated code compared to traditional human-written code. By profiling and measuring CPU, memory, and power consumption during execution in a specific context(s), we aim to identify inefficiencies in AI-generated code and highlight areas for optimization. We seek to bridge the gap between code automation and sustainable software development, offering insights into how LLMs can speed up coding and make it greener. The exact details of the thesis topic depend on the student's previous knowledge and interests.

Lõputöö kaitsmise aasta

2024-2025

Juhendaja

Hina Anwar

Suhtlemiskeel(ed)

inglise keel

Nõuded kandideerijale

Tase

Magister

Märksõnad

#SEA, #Software_Quality, #GreenAI, #Sustainable_Software, #Green_Software

 

Nimi

Hina Anwar

Tel

E-mail