Constraint checking during error recovery

The system-level software onboard a spacecraft is responsible for recovery from communication, power, thermal, and computer-health anomalies that may occur. The recovery must occur without disrupting any critical scientific or engineering activity that is executing at the time of the error. Thus, the error-recovery software may have to execute concurrently with the ongoing acquisition of scientific data or with spacecraft maneuvers. This work provides a technique by which the rules that constrain the concurrent execution of these processes can be modeled in a graph. An algorithm is described that uses this model to validate that the constraints hold for all concurrent executions of the error-recovery software with the software that controls the science and engineering activities of the spacecraft. The results are applicable to a variety of control systems with critical constraints on the timing and ordering of the events they control

Automated requirements analysis for a molecular watchdog timer

Dynamic systems in DNA nanotechnology are often programmed using a chemical reaction network (CRN) model as an intermediate level of abstraction. In this paper, we design and analyze a CRN model of a watchdog timer, a device commonly used to monitor the health of a safety critical system. Our process uses incremental design practices with goal-oriented requirements engineering, software verification tools, and custom software to help automate the software engineering process. The watchdog timer is comprised of three components: an absence detector, a threshold filter, and a signal amplifier. These components are separately designed and verified, and only then composed to create the molecular watchdog timer. During the requirements-design iterations, simulation, model checking, and analysis are used to verify the system. Using this methodology several incomplete requirements and design flaws were found, and the final verified model helped determine specific parameters for biological experiments

Population-Induced Phase Transitions and the Verification of Chemical Reaction Networks

We show that very simple molecular systems, modeled as chemical reaction networks, can have behaviors that exhibit dramatic phase transitions at certain population thresholds. Moreover, the magnitudes of these thresholds can thwart attempts to use simulation, model checking, or approximation by differential equations to formally verify the behaviors of such systems at realistic populations. We show how formal theorem provers can successfully verify some such systems at populations where other verification methods fail

Automated caching of behavioral patterns for efficient run-time

Run-time monitoring is a powerful approach for dy- namically detecting faults or malicious activity of software systems. However, there are often two obsta- cles to the implementation of this approach in prac- tice: (1) that developing correct and/or faulty be- havioral patterns can be a difficult, labor-intensive process, and (2) that use of such pattern-monitoring must provide rapid turn-around or response time. We present a novel data structure, called extended action graph, and associated algorithms to overcome these drawbacks. At its core, our technique relies on ef- fectively identifying and caching specifications from (correct/faulty) patterns learnt via machine-learning algorithm. We describe the design and implementa- tion of our technique and show its practical applicabil- ity in the domain of security monitoring of sendmail software

Experiences Using Formal Methods for Requirements Modeling

This paper describes three cases studies in the lightweight application of formal methods to requirements modeling for spacecraft fault protection systems. The case studies differ from previously reported applications of formal methods in that formal methods were applied very early in the requirements engineering process, to validate the evolving requirements. The results were fed back into the projects, to improve the informal specifications. For each case study, we describe what methods were applied, how they were applied, how much effort was involved, and what the findings were. In all three cases, the formal modeling provided a cost effective enhancement of the existing verification and validation processes. We conclude that the benefits gained from early modeling of unstable requirements more than outweigh the effort needed to maintain multiple representations

Towards Engineering Fair and Equitable Software Systems for Managing Low-Altitude Airspace Authorizations

Small Unmanned Aircraft Systems (sUAS) have gained widespread adoption across a diverse range of applications. This has introduced operational complexities within shared airspaces and an increase in reported incidents, raising safety concerns. In response, the U.S. Federal Aviation Administration (FAA) is developing a UAS Traffic Management (UTM) system to control access to airspace based on an sUAS's predicted ability to safely complete its mission. However, a fully automated system capable of swiftly approving or denying flight requests can be prone to bias and must consider safety, transparency, and fairness to diverse stakeholders. In this paper, we present an initial study that explores stakeholders' perspectives on factors that should be considered in an automated system. Results indicate flight characteristics and environmental conditions were perceived as most important but pilot and drone capabilities should also be considered. Further, several respondents indicated an aversion to any AI-supported automation, highlighting the need for full transparency in automated decision-making. Results provide a societal perspective on the challenges of automating UTM flight authorization decisions and help frame the ongoing design of a solution acceptable to the broader sUAS community

Probing the Security of DNA Origami

DNA origami is a method used to program the self-assembly of nanoscale computational systems. The contribution of this paper is to probe the security of a canonical DNA origami that is often reused. The paper describes the techniques we used to design probes whose input targets the origami systems’ integrity. Experimental results show that the probes successfully caused up to a third of the systems to fail. Moreover, our approach identified a single, small input whose addition was able to cause the failure of a quarter of the systems. Extending such probes to other DNA origami systems may aid in understanding how to enhance their reliability