Domenico Giorgio Catania
AI-Augmented Pointer Analysis for Indirect Function Call Resolution in Automotive Firmware.
Rel. Luciano Lavagno, Ippazio Martella. Politecnico di Torino, Master of science program in Electronic Engineering, 2026
Abstract
Indirect function calls through function pointers, callback registrations, and dispatch tables are pervasive in automotive embedded software, and particularly in AUTOSAR Basic Software (BSW) firmware, yet they remain outside the scope of automated verification in current safety qualification tools. This thesis addresses the gap for RTA-SQF, an ETAS safety qualification framework for AUTOSAR projects, where 399 indirect callsites across 1,648 source files are flagged for manual verification. A systematic evaluation of all eight pointer analysis algorithms provided by the Static Value-Flow (SVF) framework on the RTA-SK production firmware reveals a precision ceiling: four Andersen-family algorithms converge at 63.7% and two flow-sensitive algorithms at 63.9%, resolving at most 255 of 399 callsites.
The remaining 36.1% have empty points-to sets due to AUTOSAR configuration-time assignments, runtime-indexed dispatch, and deliberate type erasure patterns that are beyond the reach of any static analysis operating on the compiled bitcode alone
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