ArXiv TLDR

Inferring Equivalence Classes from Legacy Undocumented Embedded Binaries for ISO 26262-Compliant Testing

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2604.22673

Marco De Luca, Domenico Francesco De Angelis, Domenico Amalfitano, Pasquale Cimmino, Anna Rita Fasolino

cs.SEcs.SC

TLDR

This paper introduces a binary-level method to infer equivalence classes from legacy undocumented embedded firmware, aiding ISO 26262-compliant testing.

Key contributions

  • Proposes a binary-level method to infer output-oriented equivalence classes directly from compiled firmware.
  • Uses control-flow reconstruction and guided symbolic execution to group execution paths by observable behavior.
  • Generates human-readable representations to support comprehension and documentation of inferred classes.
  • Validated in an industrial automotive context, showing strong alignment with expert expectations and usefulness.

Why it matters

Applying equivalence class partitioning to legacy undocumented firmware is challenging due to incomplete specifications, hindering ISO 26262 compliance. This paper provides a novel binary-level solution, enabling systematic testing without source-level documentation. It significantly improves the testability and safety assurance of critical embedded systems.

Original Abstract

Equivalence class partitioning is a well-established test design technique mandated by safety standards such as ISO~26262 for systematic testing of safety software. In industrial practice, however, its application to legacy undocumented embedded firmware is often hindered by incomplete or outdated functional specifications. This paper proposes a binary-level methodology for inferring output-oriented equivalence classes directly from compiled firmware, without relying on source-level annotations or external documentation. The approach combines control-flow reconstruction and guided symbolic execution to analyze individual functions and group execution paths according to indistinguishable observable behavior, including return values and output parameters. An optional post-processing step produces human-readable representations to support comprehension and documentation. The methodology is evaluated in an industrial automotive context through a practitioner-based study assessing correctness and interpretability. Results indicate strong alignment with expert expectations and a positive perception of readability and usefulness for supporting function understanding and test design. These findings demonstrate the feasibility and practical relevance of binary-level equivalence class inference for systematic testing of legacy undocumented safety-embedded software.

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