SOURCE-LINKED INTELLIGENCE

Program-Specific Agents

CORDIS · observation · Publication date unknown

Program-Specific Agents In recent years, novel AI coding assistants based on large language models (LLMs) have become extremely popular in creating code. However, at least 50% of the effort of software development goes into understanding and maintaining existing software, tasks that still pose grand challenges for LLMs. This is because most maintenance tasks are related to the dynamic behavior of programs, which is insufficiently captured by learning from static code alone. Understanding how the individual pieces of a large program work together can take human experts months to years. As part of our ERC Advanced Grant “S3—Semantics of Software Systems”, we have developed innovative techniques to systematically _test_software systems, comprehensively exploring their behavior. This allows us to capture the dynamic features of inputs, outputs, and executions and train programspecific machine learning models that relate them to each other. The resulting model can the

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR