Validating LLM-Modernized Scientific Software Through Differential Fault Injection

• URL: http://arxiv.org/abs/2608.14527v1
• Date: Fri, 14 Aug 2026 17:45:55 GMT
• Title: Validating LLM-Modernized Scientific Software Through Differential Fault Injection
• Abstract summary: Large language model (LLM) agents are increasingly used to modernize the legacy Fortran underlying production scientific software.<n>We present a differential fault-injection validation method to test whether a modernization preserves the original code's response to faults, perturbations, and reduced precision.
• Score: 4.4455011390187815
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language model (LLM) agents are increasingly used to modernize the legacy Fortran underlying production scientific software, but validation of these transformations emphasizes nominal executions and may not test whether a modernization preserves the original code's response to faults, perturbations, and reduced precision. We present a differential fault-injection validation method: a harness instruments the shared self-consistent-field driver of GAMESS at twelve sites and applies identical, deterministic faults to the original and LLM-modernized implementations, isolating the converted integral kernels. Across more than 2,200 runs, transient-fault absorption costs match a contraction-based model (predicted slopes 0.74 and 1.49 iterations per bit; measured 0.82 and 1.50), persistent perturbations halve final-energy error per additional bit, and the campaigns expose phase-dependent parallel deadlocks and false convergence under reduced precision. The original and modernized kernels agree in all 200 paired injections, and a measurement-guided synchronization change composes with the modernization, matching in all 40 pairs.

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