Fardin Abdi

Pushpak Jagtap, Fardin Abdi, Matthias Rungger et al.

The paper addresses the issue of reliability of complex embedded control systems in the safety-critical environment. In this paper, we propose a novel approach to design controller that (i) guarantees the safety of nonlinear physical systems, (ii) enables safe system restart during runtime, and (iii) allows the use of complex, unverified controllers (e.g., neural networks) that drive the physical systems towards complex specifications. We use abstraction-based controller synthesis approach to design a formally verified controller that provides application and system-level fault tolerance along with safety guarantee. Moreover, our approach is implementable using commercial-off-the-shelf (COTS) processing unit. To demonstrate the efficacy of our solution and to verify the safety of the system under various types of faults injected in applications and in the underlying real-time operating system (RTOS), we implemented the proposed controller for the inverted pendulum and three degree-of-freedom (3-DOF) helicopter.

Fardin Abdi, Renato Mancuso, Rohan Tabish et al.

Embedded systems in safety-critical environments are continuously required to deliver more performance and functionality, while expected to provide verified safety guarantees. Nonetheless, platform-wide software verification (required for safety) is often expensive. Therefore, design methods that enable utilization of components such as real-time operating systems (RTOS), without requiring their correctness to guarantee safety, is necessary. In this paper, we propose a design approach to deploy safe-by-design embedded systems. To attain this goal, we rely on a small core of verified software to handle faults in applications and RTOS and recover from them while ensuring that timing constraints of safety-critical tasks are always satisfied. Faults are detected by monitoring the application timing and fault-recovery is achieved via full platform restart and software reload, enabled by the short restart time of embedded systems. Schedulability analysis is used to ensure that the timing constraints of critical plant control tasks are always satisfied in spite of faults and consequent restarts. We derive schedulability results for four restart-tolerant task models. We use a simulator to evaluate and compare the performance of the considered scheduling models.

Rishab Balasubramanian, Pin-Jie Lin, Rituraj Sharma et al.

We investigate whether post-trained capabilities can be transferred across models without retraining, with a focus on transfer across different model scales. We propose the Master Key Hypothesis, which states that model capabilities correspond to directions in a low-dimensional latent subspace that induce specific behaviors and are transferable across models through linear alignment. Based on this hypothesis, we introduce UNLOCK, a training-free and label-free framework that extracts a capability direction by contrasting activations between capability-present and capability-absent Source variants, aligns it with a Target model through a low-rank linear transformation, and applies it at inference time to elicit the behavior. Experiments on reasoning behaviors, including Chain-of-Thought (CoT) and mathematical reasoning, demonstrate substantial improvements across model scales without training. For example, transferring CoT reasoning from Qwen1.5-14B to Qwen1.5-7B yields an accuracy gain of 12.1% on MATH, and transferring a mathematical reasoning direction from Qwen3-4B-Base to Qwen3-14B-Base improves AGIEval Math accuracy from 61.1% to 71.3%, surpassing the 67.8% achieved by the 14B post-trained model. Our analysis shows that the success of transfer depends on the capabilities learned during pre-training, and that our intervention amplifies latent capabilities by sharpening the output distribution toward successful reasoning trajectories.

Fardin Abdi, Chien-Ying Chen, Monowar Hasan et al.

Many physical plants that are controlled by embedded systems have safety requirements that need to be respected at all times - any deviations from expected behavior can result in damage to the system (often to the physical plant), the environment or even endanger human life. In recent times, malicious attacks against such systems have increased - many with the intent to cause physical damage. In this paper, we aim to decouple the safety of the plant from security of the embedded system by taking advantage of the inherent inertia in such systems. In this paper we present a system-wide restart-based framework that combines hardware and software components to (a) maintain the system within the safety region and (b) thwart potential attackers from destabilizing the system. We demonstrate the feasibility of our approach using two realistic systems - an actual 3 degree of freedom (3-DoF) helicopter and a simulated warehouse temperature control unit. Our proof-of-concept implementation is tested against multiple emulated attacks on the control units of these systems.