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Many SAST tools sacrifice detection capabilities for performance, but CAUSEC reveals that the underlying assumptions may not hold true, challenging the status quo in security analysis.
Causal reasoning reveals that specific prompt designs can detrimentally affect code generation accuracy in LLMs, challenging assumptions about optimal input strategies.
Imagine software that autonomously evolves and maintains itself – this paper lays out the architectural groundwork for making that a reality.