An efficient algorithm for monitoring practical TPTL specifications

Dokhanchi, Adel; Hoxha, Bardh; Tuncali, Cumhur Erkan; Fainekos, Georgios

doi:10.1109/memcod.2016.7797763

Cited by 12 publications

(21 citation statements)

References 19 publications

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“…Such a requirement can be defined as a Timed Propositional Temporal Logic (TPTL) specification. TPTL is a generalization of STL which is also supported in our framework [63].…”

Section: B Development Process Supportmentioning

confidence: 77%

Requirements-Driven Test Generation for Autonomous Vehicles With Machine Learning Components

Tuncali

Fainekos

Prokhorov³

et al. 2020

IEEE Trans. Intell. Veh.

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Autonomous vehicles are complex systems that are challenging to test and debug. A requirements-driven approach to the development process can decrease the resources required to design and test these systems, while simultaneously increasing the reliability. We present a testing framework that uses signal temporal logic (STL), which is a precise and unambiguous requirements language. Our framework evaluates test cases against the STL formulae and additionally uses the requirements to automatically discover test cases that fail to satisfy the requirements. One of the key features of our tool is the support for machine learning (ML) components in the system design, such as deep neural networks. The framework allows evaluation of the control algorithms, including the ML components, and it also includes models of CCD camera, lidar, and radar sensors, as well as the vehicle environment. We use multiple methods to generate test cases, including covering arrays, which is an efficient method to search discrete variable spaces. The resulting test cases can be used to debug the controller design by identifying controller behaviors that do not satisfy requirements. The test cases can also enhance the testing phase of development by identifying critical corner cases that correspond to the limits of the system's allowed behaviors. We present STL requirements for an autonomous vehicle system, which capture both component-level and systemlevel behaviors. Additionally, we present three driving scenarios and demonstrate how our requirements-driven testing framework can be used to identify critical system behaviors, which can be used to support the development process.

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“…Such a requirement can be defined as a Timed Propositional Temporal Logic (TPTL) specification. TPTL is a generalization of STL which is also supported in our framework [63].…”

Section: B Development Process Supportmentioning

confidence: 77%

Requirements-Driven Test Generation for Autonomous Vehicles With Machine Learning Components

Tuncali

Fainekos

Prokhorov³

et al. 2020

IEEE Trans. Intell. Veh.

Self Cite

View full text Add to dashboard Cite

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“…The main feature of SCOPE is that atoms are always related to channel events, i.e., Boolean conditions that become true when specific values are transmitted over channels. We consider two kinds of events: untimed events do not have a time delay associated with them, e.g., the atom (BatteryReader, BatteryLevel, m [ We give here a brief and mostly informal account about the semantics of SCOPE, leaving the details to [37] from which we borrow the notation and the definitions. The meaning of SCOPE constraints is given in terms of timed state sequences generated by channel system like the one described in Section IV and shown in Figure 2.…”

Section: A From Requirements To Formal Propertiesmentioning

confidence: 99%

Section: A From Requirements To Formal Propertiesmentioning

confidence: 99%

“…According to [37] we write ρ |= ϕ to denote that the SCOPE constraint ϕ is sastified by the TSS ρ. This relationship is formally described for TPTL in [37] and thus holds also for our fragment SCOPE. Intuitively, Boolean formulas are satisfied at any point i ∈ N of a TSS if the evaluation σ i makes the formula true, and temporal connectives have the usual meaning: next α is satisfied at a point in time if α is satisfied at the next one; α until β is satisfied if α holds until β eventually does.…”

Section: A From Requirements To Formal Propertiesmentioning

confidence: 99%

“…In [37] a general monitoring algorithm for TPTL properties is described. We could resort to that procedure in order to obtain monitors from properties written in SCOPE.…”

Section: B From Formal Properties To Runtime Monitorsmentioning

confidence: 99%

See 2 more Smart Citations

Formalizing the Execution Context of Behavior Trees for Runtime Verification of Deliberative Policies

Colledanchise,

Cicala,

Domenichelli

et al. 2021

Preprint

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Our research aims to enable automated property verification of deliberative components in robot control architectures. We focus on a formalization of the execution context of Behavior Trees (BTs) to provide a scalable, yet formally grounded, methodology to enable runtime verification and prevent unexpected robot behaviors to hamper deployment. To this end, we consider a message-passing model that accommodates both synchronous and asynchronous composition of parallel components, in which BTs and other components execute and interact according to the communication patterns commonly adopted in robotic software architectures. We introduce a formal property specification language to encode requirements and build runtime monitors. We performed a set of experiments both on simulations and on the real robot, demonstrating the feasibility of our approach in a realistic application, and its integration in a typical robot software architecture. We also provide an OS-level virtualization environment to reproduce the experiments in the simulated scenario.

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