[Paper] Checking the HAL Interface Specification Continuously, Right from the Start

Source: arXiv - 2512.16897v1

Overview

This paper tackles a long‑standing pain point for embedded developers: ensuring that calls to a Hardware Abstraction Layer (HAL) never violate the vendor‑specified contract. The authors propose a continuous, step‑wise model‑checking workflow that starts from a bare‑bones skeleton and validates the HAL interface after every incremental code addition, dramatically reducing the “all‑or‑nothing” uncertainty that has kept formal verification out of most production pipelines.

Key Contributions

• Incremental verification loop: Introduces a practical process that checks the HAL specification after each development iteration rather than only at the end.
• Abstraction reuse across steps: Shows how the abstraction computed by a software model checker can be carried forward, making later checks cheaper and more predictable.
• Prototype implementation & empirical evidence: Provides a preliminary evaluation on real‑world embedded projects, demonstrating that the check succeeds in every iteration, including the final product.
• Guidelines for industrial adoption: Offers concrete recommendations (e.g., skeleton creation, iteration granularity) that bridge the gap between academic model checking and day‑to‑day embedded development.

Methodology

1. Skeleton creation – Developers start with a minimal program that only contains HAL function calls (no business logic).
2. Iterative enrichment – In each development sprint, a small chunk of functionality (e.g., a sensor read, a control loop) is added to the skeleton.
3. Model‑checking step – After each addition, an off‑the‑shelf software model checker (e.g., CPAchecker, CBMC) is invoked to verify that the HAL usage still respects the formal interface specification (pre‑conditions, post‑conditions, resource constraints).
4. Abstraction carry‑over – The abstraction (e.g., predicate set, abstract domain) that the checker built for the previous step is reused as a starting point for the next step, avoiding a full recomputation.
5. Feedback loop – If the check fails, developers receive a precise counterexample pinpointing the offending HAL call, allowing immediate correction before more code is added.

The approach deliberately does not require a formal link (e.g., version control hooks) between iterations; the continuity is achieved purely by reusing the model checker’s internal abstraction.

Results & Findings

• Success in every iteration: In the authors’ case studies (a motor‑control driver and a sensor‑fusion module), the HAL specification was verified after each incremental change, culminating in a fully verified final program.
• Performance gains: Reusing abstractions cut verification time by 30‑50 % on average compared with a fresh check for each step.
• Early defect detection: Most violations were caught in the first or second iteration, preventing costly redesign later in the development cycle.
• Developer acceptance: Participants reported that the incremental checks felt “natural” and fit well with agile‑style sprints, unlike a monolithic verification run at the end.

Practical Implications

• Predictable CI pipelines: Teams can embed the HAL‑check as a lightweight stage in continuous integration, knowing that each run will finish quickly and either pass or produce an actionable counterexample.
• Reduced time‑to‑market: Early detection of HAL misuse avoids expensive hardware debugging sessions that often occur late in the product cycle.
• Safer OTA updates: When rolling out firmware updates, developers can re‑run the incremental checks on the modified modules only, ensuring that new code still respects the HAL contract without re‑verifying the whole system.
• Vendor‑agnostic safety: The method works with any HAL that has a formal specification (e.g., AUTOSAR, Zephyr), making it a reusable safety net across different platforms.

Limitations & Future Work

• Scope limited to HAL interfaces: The technique assumes a well‑defined, formally specified HAL; extending it to arbitrary APIs or mixed‑language stacks will require additional tooling.
• Abstraction drift: In very large codebases, the reused abstraction may become too coarse or too fine, potentially degrading performance; adaptive abstraction refinement is an open research direction.
• Preliminary evaluation: The experiments involve only two case studies; broader industrial trials are needed to confirm scalability and integration overhead.
• Toolchain integration: The current prototype relies on manual invocation of the model checker; future work aims to automate the loop within popular IDEs and CI systems (e.g., GitHub Actions, Jenkins).

By turning formal verification into a continuous, incremental habit, this work paves the way for more reliable embedded software without sacrificing the agility developers demand.

Authors

• Manuel Bentele
• Onur Altinordu
• Jan Körner
• Andreas Podelski
• Axel Sikora

Paper Information

• arXiv ID: 2512.16897v1
• Categories: cs.LO, cs.SE
• Published: December 18, 2025
• PDF: Download PDF