Test-time, Run-time, and Simulation-time Temporal Assertions in RSPCreation and Validation of Embedded Assertion Statecharts

Proceedings of the 16th International Workshop on Rapid System Prototyping (RSP’05)For cost-effective prototyping, system designers should have a clear understanding of the intended use of the prototype under development. This paper describes a classification of formal specification (temporal) assertions used during system prototyping. The classification introduces two new classes of assertions in addition to the well-known class of test-time assertions: (i) assertions used only during simulation, and (ii) deployable assertions integrated with run-time control flow. Separating the formal specification into three distinct classes allows system designers to de- velop more effective prototypes to evaluate the different system behaviors and constraints. A prototype of a naval torpedo system is used to illustrate the concept.The research reported in this article was funded in part by a grant from the U.S. Missile Defense Agency

Statistical Runtime Checking of Probabilistic Properties

Probabilistic correctness is an important aspect of reliable systems. A soft real-time system, for instance, may be designed to tolerate some degree of deadline misses under a threshold. Since probabilistic systems may behave differently from their probabilistic models depending on their current environments, checking the systems at runtime can provide another level of assurance for their probabilistic correctness. This paper presents a statistical runtime verification for probabilistic properties using statistical analysis. However, while this statistical analysis collects a number of execution paths as samples to check probabilistic properties within some certain error bounds, runtime verification can only produce one single sample. This paper provides a technique to produce such a number of samples and applies this methodology to check probabilistic properties in wireless sensor network applications

On-line Monitoring of Metric Temporal Logic with Time- Series Constraints Using Alternating Finite Automata

In this paper we describe a technique for monitoring and checking temporal logic assertions augmented with real-time and time-series constraints, or Metric Temporal Logic Series (MTLS). The method is based on Remote Execution and Monitoring (REM) of temporal logic assertions. We describe the syntax and semantics of MTLS and a monitoring technique based on alternating finite automata that is efficient for a large set of frequently used formulae and is also an on-line technique. We investigate the run-time data-structure size for several interesting assertions taken from the Kansas State specification patterns

Towards Real-Time, On-Board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS

Adventures in monitorability: From branching time to linear time and back again.

This paper establishes a comprehensive theory of runtime monitorability for Hennessy-Milner logic with recursion, a very expressive variant of the modal µ-calculus. It investigates the monitorability of that logic with a linear-time semantics and then compares the obtained results with ones that were previously presented in the literature for a branching-time setting. Our work establishes an expressiveness hierarchy of monitorable fragments of Hennessy-Milner logic with recursion in a linear-time setting and exactly identifies what kinds of guarantees can be given using runtime monitors for each fragment in the hierarchy. Each fragment is shown to be complete, in the sense that it can express all properties that can be monitored under the corresponding guarantees. The study is carried out using a principled approach to monitoring that connects the semantics of the logic and the operational semantics of monitors. The proposed framework supports the automatic, compositional synthesis of correct monitors from monitorable properties

Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS